This is going to be an attempt to create a machine learning algorithm to predict whether or not a stock is worth buying based on a "elo score". When looking to buy a stock on may use indicators the help such as MacD, RSI, Bollinger Bands etc. I believe we are subconsciously creating an algorithm to make that split buy/sell decision. The result of the algorithm is what I call the Elo score and I am trying to discover how that score is calculated.

1. First create a folder for this project
2. Use your command line of choice to navigate to the folder. I am using cmder
3. Once you are in your folder you dedicated to the project you are going to then use the command: git clone https://github.com/Cantum2/StockMetaScore.git
4. Now add the project folder in to your editor of choice
5. Great you should have everything installed!

Their are thousands of wonderful tools in the world for projects like these! I am using which are not required I just found them useful:

1. Pycharm: The editor of choice for this project
2. cmder: This is a command line for windows that has a lovely UI

1. I will be using most everything from SciPy
2. Tensorflow

This is my first machine learning project and first decent sized python project so there might be some situations where best practices are not followed but I am learning and will adopt best practices as I learn them.

Marcus Cantu