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.
- First create a folder for this project
- Use your command line of choice to navigate to the folder. I am using cmder
- 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 - Now add the project folder in to your editor of choice
- 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:
- Pycharm: The editor of choice for this project
- cmder: This is a command line for windows that has a lovely UI
- I will be using most everything from SciPy
- 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