Every Day Pips – Forex Manual System - Forex Robot Nation

Looking back 18 months.

I was going through old emails today and came across this one I sent out to family on January 4, 2018. It was a reflection on the 2017 crypto bull market and where I saw it heading, as well as some general advice on crypto, investment, and being safe about how you handle yourself in cryptoland.
I feel that we are on the cusp of a new bull market right now, so I thought that I would put this out for at least a few people to see *before* the next bull run, not after. While the details have changed, I don't see a thing in this email that I fundamentally wouldn't say again, although I'd also probably insist that people get a Yubikey and use that for all 2FA where it is supported.
Happy reading, and sorry for some of the formatting weirdness -- I cleaned it up pretty well from the original email formatting, but I love lists and indents and Reddit has limitations... :-/
Also, don't laught at my token picks from January 2018! It was a long time ago and (luckliy) I took my own advice about moving a bunch into USD shortly after I sent this. I didn't hit the top, and I came back in too early in the summer of 2018, but I got lucky in many respects.
----------------------------------------------------------------------- Jan-4, 2018
Hey all!
I woke up this morning to ETH at a solid $1000 and decided to put some thoughts together on what I think crypto has done and what I think it will do. *******, if you could share this to your kids I’d appreciate it -- I don’t have e-mail addresses, and it’s a bit unwieldy for FB Messenger… Hopefully they’ll at least find it thought-provoking. If not, they can use it as further evidence that I’m a nutjob. 😉
Some history before I head into the future.
I first mined some BTC in 2011 or 2012 (Can’t remember exactly, but it was around the Christmas holidays when I started because I had time off from work to get it set up and running.) I kept it up through the start of summer in 2012, but stopped because it made my PC run hot and as it was no longer winter, ********** didn’t appreciate the sound of the fans blowing that hot air into the room any more. I’ve always said that the first BTC I mined was at $1, but looking back at it now, that’s not true – It was around $2. Here’s a link to BTC price history.
In the summer of 2013 I got a new PC and moved my programs and files over before scrapping the old one. I hadn’t touched my BTC mining folder for a year then, and I didn’t even think about salvaging those wallet files. They are now gone forever, including the 9-10BTC that were in them. While I can intellectually justify the loss, it was sloppy and underlines a key thing about cryptocurrency that I believe will limit its widespread adoption by the general public until it is addressed and solved: In cryptoland, you are your own bank, and if you lose your password or account number, there is no person or organization that can help you reset it so that you can get access back. Your money is gone forever.
On April 12, 2014 I bought my first BTC through Coinbase. BTC had spiked to $1000 and been in the news, at least in Japan. This made me remember my old wallet and freak out for a couple of months trying to find it and reclaim the coins. I then FOMO’d (Fear Of Missing Out”) and bought $100 worth of BTC. I was actually very lucky in my timing and bought at around $430. Even so, except for a brief 50% swing up almost immediately afterwards that made me check prices 5 times a day, BTC fell below my purchase price by the end of September and I didn’t get back to even until the end of 2015.
In May 2015 I bought my first ETH at around $1. I sent some guy on bitcointalk ~$100 worth of BTC and he sent me 100 ETH – all on trust because the amounts were small and this was a small group of people. BTC was down in the $250 range at that point, so I had lost 30-40% of my initial investment. This was of the $100 invested, so not that much in real terms, but huge in percentages. It also meant that I had to buy another $100 of BTC on Coinbase to send to this guy. A few months after I purchased my ETH, BTC had doubled and ETH had gone down to $0.50, halving the value of my ETH holdings. I was even on the first BTC purchase finally, but was now down 50% on the ETH I had bought.
The good news was that this made me start to look at things more seriously. Where I had skimmed white papers and gotten a superficial understanding of the technology before FOMO’ing, I started to act as an investor, not a speculator. Let me define how I see those two different types of activity:
So what has been my experience as an investor? After sitting out the rest of 2015 because I needed to understand the market better, I bought into ETH quite heavily, with my initial big purchases being in March-April of 2016. Those purchases were in the $11-$14 range. ETH, of course, dropped immediately to under $10, then came back and bounced around my purchase range for a while until December of 2016, when I purchased a lot more at around $8.
I also purchased my first ICO in August of 2016, HEAT. I bought 25ETH worth. Those tokens are now worth about half of their ICO price, so about 12.5ETH or $12500 instead of the $25000 they would be worth if I had just kept ETH. There are some other things with HEAT that mean I’ve done quite a bit better than those numbers would suggest, but the fact is that the single best thing I could have done is to hold ETH and not spend the effort/time/cost of working with HEAT. That holds true for about every top-25 token on the market when compared to ETH. It certainly holds true for the many, many tokens I tried to trade in Q1-Q2 of 2017. In almost every single case I would have done better and slept better had I just held ETH instead of trying to be smarter than Mr. Market.
But, I made money on all of them except one because the crypto market went up more in USD terms than any individual coin went down in ETH or BTC terms. This underlines something that I read somewhere and that I take to heart: A rising market makes everyone seem like a genius. A monkey throwing darts at a list of the top 100 cryptocurrencies last year would have doubled his money. Here’s a chart from September that shows 2017 year-to-date returns for the top 10 cryptocurrencies, and all of them went up a *lot* more between then and December. A monkey throwing darts at this list there would have quintupled his money.
When evaluating performance, then, you have to beat the monkey, and preferably you should try to beat a Wall Street monkey. I couldn’t, so I stopped trying around July 2017. My benchmark was the BLX, a DAA (Digital Asset Array – think fund like a Fidelity fund) created by ICONOMI. I wasn’t even close to beating the BLX returns, so I did several things.
  1. I went from holding about 25 different tokens to holding 10 now. More on that in a bit.
  2. I used those funds to buy ETH and BLX. ETH has done crazy-good since then and BLX has beaten BTC handily, although it hasn’t done as well as ETH.
  3. I used some of those funds to set up an arbitrage operation.
The arbitrage operation is why I kept the 11 tokens that I have now. All but a couple are used in an ETH/token pair for arbitrage, and each one of them except for one special case is part of BLX. Why did I do that? I did that because ICONOMI did a better job of picking long-term holds than I did, and in arbitrage the only speculative thing you must do is pick the pairs to trade. My pairs are (No particular order):
I also hold PLU, PLBT, and ART. These two are multi-year holds for me. I have not purchased BTC once since my initial $200, except for a few cases where BTC was the only way to go to/from an altcoin that didn’t trade against ETH yet. Right now I hold about the same 0.3BTC that I held after my first $100 purchase, so I don’t really count it.
Looking forward to this year, I am positioning myself as follows:
Looking at my notes, I have two other things that I wanted to work into this email that I didn’t get to, so here they are:
  1. Just like with free apps and other software, if you are getting something of value and you didn’t pay anything for it, you need to ask why this is. With apps, the phrase is “If you didn’t pay for the product, you are the product”, and this works for things such as pump groups, tips, and even technical analysis. Here’s how I see it.
    1. People don’t give tips on stocks or crypto that they don’t already own that stock or token. Why would they, since if they convince anyone to buy it, the price only goes up as a result, making it more expensive for them to buy in? Sure, you will have friends and family that may do this, but people in a crypto club, your local cryptocurrency meetup, or online are generally not your friends. They are there to make money, and if they can get you to help them make money, they will do it. Pump groups are the worst of these, and no matter how enticing it may look, stay as far away as possible from these scams. I even go so far as to report them when I see them advertise on FB or Twitter, because they are violating the terms of use.
    2. Technical analysis (TA) is something that has been argued about for longer than I’ve been alive, but I think that it falls into the same boat. In short, TA argues that there are patterns in trading that can be read and acted upon to signal when one must buy or sell. It has been used forever in the stock and foreign exchange markets, and people use it in crypto as well. Let’s break down these assumptions a bit.
i. First, if crypto were like the stock or forex markets we’d all be happy with 5-7% gains per year rather than easily seeing that in a day. For TA to work the same way in crypto as it does in stocks and foreign exchange, the signals would have to be *much* stronger and faster-reacting than they work in the traditional market, but people use them in exactly the same way.
ii. Another area where crypto is very different than the stock and forex markets centers around market efficiency theory. This theory says that markets are efficient and that the price reflects all the available information at any given time. This is why gold in New York is similar in price to gold in London or Shanghai, and why arbitrage margins are easily <0.1% in those markets compared to cryptoland where I can easily get 10x that. Crypto simply has too much speculation and not enough professional traders in it yet to operate as an efficient market. That fundamentally changes the way that the market behaves and should make any TA patterns from traditional markets irrelevant in crypto.
iii. There are services, both free and paid that claim to put out signals based on TA for when one should buy and sell. If you think for even a second that they are not front-running (Placing orders ahead of yours to profit.) you and the other people using the service, you’re naïve.
iv. Likewise, if you don’t think that there are people that have but together computerized systems to get ahead of people doing manual TA, you’re naïve. The guys that I have programming my arbitrage bots have offered to build me a TA bot and set up a service to sell signals once our position is taken. I said no, but I am sure that they will do it themselves or sell that to someone else. Basically they look at TA as a tip machine where when a certain pattern is seen, people act on that “tip”. They use software to see that “tip” faster and take a position on it so that when slower participants come in they either have to sell lower or buy higher than the TA bot did. Remember, if you are getting a tip for free, you’re the product. In TA I see a system when people are all acting on free preset “tips” and getting played by the more sophisticated market participants. Again, you have to beat that Wall Street monkey.
  1. If you still don’t agree that TA is bogus, think about it this way: If TA was real, Wall Street would have figured it out decades ago and we would have TA funds that would be beating the market. We don’t.
  2. If you still don’t agree that TA is bogus and that its real and well, proven, then you must think that all smart traders use them. Now follow that logic forward and think about what would happen if every smart trader pushing big money followed TA. The signals would only last for a split second and would then be overwhelmed by people acting on them, making them impossible to leverage. This is essentially what the efficient market theory postulates for all information, including TA.
OK, the one last item. Read this weekly newsletter – You can sign up at the bottom. It is free, so they’re selling something, right? 😉 From what I can tell, though, Evan is a straight-up guy who posts links and almost zero editorial comments.
Happy 2018.
submitted by uetani to CryptoCurrency [link] [comments]

WaykiChain/WICC- Helpful Information to Get Started

WaykiChain/WICC- Helpful Information to Get Started
Welcome to WICCProject!
To follow WaykiChain's channels, please check the link under the comment with silver badge.

Catalogue

1. What Is WaykiChain?
2. Where is WaykiChain heading?
3. WaykiChain’s Technology
4. How does WaykiChain work?
5. WaykiChain’s Applications &Dapps
6. What is WICC? How to Buy WICC?
7. What is the use of WICC?
8. What are WaykiChain's advantages as a public chain 3.0?
9. FAQ
10. Contents Expected to Read About WaykiChain

1. What Is WaykiChain?
Born in Jan. 2017, Waykichain is a 3rd generation public chain with DPoS consensus mechanism. The transaction speed can keep above 1000 TPS in actual use. WaykiBet1.0, build on WaykiChain and launched in May 13, 2018 is the first ever prediction DApp based on public chain with over 130,000 downloads. The DApp has now been updated to V2.5.
WaykiChain as a team focuses on blockchain technology development and community related operations. We are committed to building a decentralized, community self-governance big platform and big ecosystem, and we are moving toward it with nearly 1 million community members.

2. Where is WaykiChain Heading?
The future of WaykiChain is a big community-driven public chain ecosystem. WaykiChain aims to build a decentralized application platform that can provide users with complete blockchain-powered smart contract system. Anyone can realize their business ideas on WaykiChain and develop their own DApp, and build their own brands.
WaykiChain takes decentralized prediction, assets trading and forex trading as entry points to expand markets in the early stage. After accumulating plenty of application users and developers, WaykiChain will gradually perfect its upper blockchain applications.
Currently, WaykiChain tech team is focusing on underlying public chain development. WaykiChain will provide friendly development environment to developers with sufficient development templates an interfaces. Besides, WaykiChain team plans to take a part of WICC as reward those developers who have made important contributions to the community. WaykiChain is committed to building an underlying technology platform that truly integrates blockchain application and real business. Along with its development, WaykiChain will gradually grow into a big ecosystem with totally decentralized operations, and brings the convenience of blockchain to every user.

3. WaykiChain’s Technology
  • High Performance and Expandability
WaykiChain is a public blockchain with high concurrent processing capability and generates a new block at a fixed interval of 10 seconds. Through rigorous engineering tests, the average transaction throughput is verified as 1000+ TPS for coin transfer transactions and 100+ TPS for smart contract based transactions.

  • Consensus Mechanism
WaykiChain adopts Delegated Proof of Stake (DPoS) as the blockchain consensus mechanism since it is most energy efficient, offering high transaction throughput while maintaining a certain level of community driven decentralization.
There are in total 11 ledger nodes (i.e. block producers), responsible for validating and packing all network submitted transactions into blocks. During block creation, a ledger node collects reward tokens that are carried within each transaction. The 11 ledeger nodes take turns in block creation by the time interval of 10 seconds and the sequence of whom to do block creation at a specific time slot is randomized to avoid prediction by external observers.
The overall network could experience infrequent hard forks due to network or ledger node performance instability. However, the robust consensus algorithm allows a quick recovery from one or several hard forks by resorting to a unified single longest fork and the network will thence stabilize and perform steadily again.

  • Vote Mechanism
The 11 ledger nodes are elected through a never-ending voting process. Individual coin holders can cast their votes to the candidate ledger nodes. Each vote can be cast for up to 11 candidate ledger nodes. By so doing, the amout of WICC coins which is equal to the the amount of votes will be locked into the network, similar to bank saving activities. By the next voting events (i.e. increase or decrease the votes, vote for new candiates) a certain amount of interest coins will be newly generated and released to the person who previously cast votes to the candidates. The interest rate plan goes as follows: the first year’s interest rate is 5%, it will decrease by 1% annually in following years. Once it reaches 1% as the interest rate, it will stablize as 1% for all the subsequent years.
The top 11 candidates who recieved the top most votes cast by community coin holders automatically becomes the ledger nodes and take turns with certain randomness by a random perturbation algorithm to do the block creation by validing and packing the transactions into a new block.
  • Technology Architecture of WaykiChain Ecosystem
WaykiChain aims to develop its underlying public chain technology into a big ecosystem, so that numerous industries can build their own applications and services based on WaykiChain public chain. WaykiChain has set up the following technology architecture, as shown in the image below
https://preview.redd.it/lcj249b8qr621.png?width=1219&format=png&auto=webp&s=0f6506ba2f57d0b32291c0ba741895a4ddaca735
WaykiChain core technology team is committed to providing the develop-friendly interfaces of each layer and improving the technical documentation to help the community better build the ecosystem.
  • Smart Contracts
WaykiChain's smart contracts are written in Lua scripts and processed within Lua Virtual Machine engine. Lua's various libraries are built in for developers to leverage. Due to the openess and compleness of Lua script and its liabrary provided in WaykiChain software, developers can build many forms of appliations that meet the requirements of Turing-complete computing scenarios. Lua scripting is relatively simple and requires no pre-compilation, and is thus also easier to deploy compared to other smart contract implmentation.

4. How Does WaykiChain Work?
WaykiChain uses a DPoS consensus mechanism with eleven accounting nodes. The annual rate of return is 5% for the first year, with a 1% increase with every year that goes by. Each time a block is created, an accounting node is randomly associated. The accounting node gains all of the transaction fees in its accounting block. Users can earn interest by locking WaykiChain coins. The interest is automatically determined each time the votes for the corresponding user account change.
The terms of betting are triggered by the initiator through smart contract transactions. Users can initiate various betting contract transactions, all of which can be searched and identified in the block browsers. When the betting is over, the bet initiation will publish the final results and the gaining will be then shared accordingly. In short, the betting revenue is automatically issued to the user’s wallet after the betting results are displayed.
The smart contract provided by the platform makes it possible for asset initiations to create dividend sharing rules. These rules are only triggered by various conditions. Hence, the final price of the assets in circulation will be determined by the market’s behavior towards the object in the transaction.

5. WaykiChain’s Applications &Dapps
  • Token System
Waykichain Token, WICC is a token only used and circulated in WaykiChain Wallet on our DApps. WICC itself does not have any FIAT characteristics. By consuming WICC as a kind of fuel, users can use applications on WaykiChain; by locking their WICC for a certain period of time, users can share the revenue from WICC Lock Revenue Sharing Plan; and by voting for effective and stable accounting nodes, users can earn related interest. WICC can be obtained by participating in the lock plan, by accounting, voting, and subscription, or by trading with other holders. This means WICC will be listed on lots of exchanges and traded with other cryptocurrencies, thus WICC also has trade value.

  • Decentralized App- WaykiBet
BACKGROUND- The first smart contract based application delivered by WaykiChain’s team is the WaykiChain decentralized betting application. In this application, the smart contract will assign a time duration in which the user can engage in the betting process. All the conditions related to betting will be given. When a bet is finished, the contract will release the results. The smart contract will then reward the winners.
This DApp was launched in May 2018, attracting over 130,000 users to download and bet and has been upgraded to V2.1 ever since. The latest product WaykiBet DApp V2.5 is planned to launch in November along with a new WaykiChain wallet.
INTRODUCTION- WaykiBet is a DApp developed on WaykiChain that allows strangers to build betting transactions without a trust base. WaykiBet has lowered the barriers for users by using smart contracts to deliver payout automatically, and recording transactions on blockchain with zero handling fee, providing users the best and fairest betting experience.
Everyone Can Build a Bet
More flexible: With smart contract, WaykiBet works like a betting contract exchange and everyone can build their own bets.
Fixed Odds
More interesting: Effectively avoid the fluctuations brought by floating odds in some less popular games.
Betting with Odds Ranking
More intense: Betting builders compete via odds ranking, and users can freely choose odds.
Smart Contract to Deliver Payout
More fairness: Winning of a bet will automatically trigger the blockchain smart contract to deliver the payout, without manual participation in the whole process.
Betting Records on Blockchain
More transparent: All betting transactions are recorded on blockchain and can be traced by everyone, which is totally open and transparent.

  • Decentralized App- WaykiTimes
The new WaykiChain wallet, named as WaykiTimes, will retain the original wallet functions, such as Lock Revenue Sharing and node voting. In addition, WaykiTimes is mainly designed for WaykiChain and cryptocurrency investors, developers and business partners. In addition to its wallet function, WaykiTimes has also added news and community modules. WaykiTimes is the one and only official platform for you to get thorough information of WaykiChain project. In WaykiTimes, you can easily get to know the latest WaykiChain updates, freely post and comment in community, and discuss hot topics with other crypto enthusiasts. At the same time, WaykiTimes also has WICC transfer and lock functions.

  • WaykiChain Block Explorer
WaykiChain official block explorer is a data display system for WaykiChian applications, which displays the WICC transfer and transaction records, account balances, prediction games transactions, and payout results according to application data on the blockchain. All data is open and transparent and inherently irreversible.

6. What is WICC? How to Buy WICC?
WICC is the token launched by WaykiChain. In order to buy WaykiChain (WICC), we recommend you to buy some BTC or ETH (the highest volume trading pairs) from an exchange that accepts them. Then, you will have to find a marketplace that sells WICC in exchange for the aforementioned cryptocurrencies. We recommend you to buy WICC at AEX or Huobi Exchange (AEX and Huobi has already supported WICC mainnet migration). For more information on this matter, you can visit CoinMarketCap.
When it comes to storing your WICC coins, it’s recommended that you use the wallet function on WaykiTimes V2.0 or WaykiBetV2.5. By consuming the tokens, you can also use various applications on WaykiChain.

7. What is the use of WICC?
WICC is a token used and circulated in WaykiChain Wallet on our DApps. WICC itself does not have any FIAT characteristics. By consuming WICC as a kind of fuel, users can use applications on WaykiChain; by locking their WICC for a certain period of time, users can share the revenue from WICC lock plan; and by voting for effective and stable accounting nodes, users can earn related interest. WICC can be obtained by participating in the lock plan, by accounting, voting, and subscription, or by trading with other holders. WICC has been listed on over 100 exchanges and trading with other cryptocurrencies for almost 1 year, thus WICC also has trade value.

8. What are WaykiChain's advantages as a public chain 3.0?
The first one would be the low entry barrier to our eco-system. For developers or Dapp operators they do not need to develop from the chain directly, instead, they only need to develop from the template we published. Even if you are not able to find a team of developers who understand blockchain, you can still deploy the Dapp and run it to make profit. And Waykichain will benefit from all transactions happened since you made this chain active.
The second advantage is the product it-self. WaykiBet2.5 is user-friendly to those who do not understand crypto-currency or blockchain technology.
In WaykiBet, we initiate a stablecoin using the mechanism like BitShare. The Dapp runners or some acceptance dealer need to pledge some WICC to the smart contract and get stablecoin. By doing this, users can directly buy the stable coin in the Dapp with fiat money, instead of going to the crypto exchange.
Moreover, WaykiChain designed a mix of centralized and de-centralized technical structure. By doing this, users don’t need to pay for the gas but the smart contract owner. Moreover, the performance of the entire system can be improved without losing the public creditability. The whole process, being centralized and recorded, can be verified and tracked. Theoretically, this mixed-structure can afford more parrelled transactions at the same time than all other decentralized system.

9. FAQ
  • What is WaykiChain decentralized betting application?
WaykiChain decentralized betting application is the first smart contract application launched by WaykiChain team. Each betting is triggered by the application developer via a smart contract. During the period specified in the contract, the users can initiate betting transaction, and all betting records can be traced on the blockchain browser and can never be tampered with. The smart contract will automatically reward the winners based on the final result. WaykiChain will use smart contract to automatically execute the game rule on its public chain. Instead of relying on trust between people, WaykiChain betting application adopts trust among machines to save credit costs, and guarantees full compliance with the rules setting. Besides WaykiChain Official, the developers of the decentralized applications can be any other third-parties. WaykiChain welcomes all developers to join.

  • What is WaykiChain Address?
WaykiChain address is a 34-bit string consisting of English letters and numbers that may look like digital gibberish. My WaykiChain address WXv6xP8yVW4PkZ3DPvxqfBtfz7Bof1RJHm, as an example, looks like this. All transfer records for each WaykiChain address can be found through the blockchain explorer. The address is a personal WaykiChain account like your bank account number. Anyone can transfer WICC to you via your WaykiChain address. How do I get my own WaykiChain address then? You can download a WaykiChain Wallet on WaykiChain official website, or register one on trading platforms. Each user's WaykiChain address is unique. It should be noted that each WaykiChain wallet can only create one address, therefore the wallet mnemonics must be kept carefully.

  • What is WaykiChain mainnet migration?
WaykiChain (WICC) mainnet migration is the process of replacing the previous Ethereum-based token ERC20 TOKEN with WaykiChain mainnet token. WaykiChain public chain, through several months of testing and rigorous evaluation from the exchange platforms after its release, has been fully proven to operate efficiently and stably. Mainnet migration marks that WaykiChain public chain is actually putting into use. After the mainnet migration, various applications and developments based on WaykiChain can be launched, and the service period of WaykiChain public chain truly starts. The dividend mechanism, voting mechanism, gas consumption, and accounting fees on WaykiChain ecosystem are all completed by the mainnet token. The previous ERC20 tokens do not have these functions.
By the end of June 26th, AEX Exchange, Huobi, CEO Exchange, Bying Wallet etc. and 23 exchanges in total have supported WICC mainnet migration. There will be more exchanges and wallets supporting the migration in the future. Please follow WaykiChain's channels for more details.

  • Are there any requirements or restrictions for developing projects on WaykiChain?
WaykiChain's code is completely open. WaykiChain welcomes third parties worldwide to develop, carry and operate various application products on WaykiChain, and finally form a diversiform public chain community ecology. WaykiChain is happy to provide public chain technology support for any individuals or third parties. Applications developed and operated by third parties, based on WaykiChain public chain, need to comply with local laws and policies. Only after obtaining related licenses, permits or qualifications required by local laws and policies, developers and operators can launch and operate their applications on WaykiChain. Because of blockchain public chain's globality, anonymity, open code, and the limitation of our ability, WaykiChain Official cannot judge the identity of third parties, nor have the ability and right to verify, supervise, control or interfere the third parties. Therefore, third parties should bear responsibility of their own actions.

10. Contents Expected to Read About WaykiChain
It would be great to create a post for everyone by posting what they want to have for future releases of the Waykichain DApp or anything related to using Waykichain. Therefore, please comment under this thread about your interested contents or create a post directly to express your perspective on WaykiChain.

submitted by zcatmew to WICCProject [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

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  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

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  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

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