TLDR: In stock markets, past performance is not always a good predictor of future returns, and this makes predicting stock prices using machine learning difficult. Nonetheless, you can find my attempt here.
*Prerequisite: familiarity with Python
Machine learning (ML) can be difficult to comprehend due to the jargon and math involved. In this article, I am going to try to stay as simple and DRY as possible, meaning I will make references to existing resources wherever applicable, rather than rewriting them. I incorporated the questions that I had when I was studying this topic. I hope they explain some of the questions that you might have. By the end of the article, I hope you can (1) gain general understanding of how ML works and (2) build a simple stock trading ML algorithm. Note that it is not our goal to make profit at this time. Our first step would be to apply ML to predict stock prices. However, I did compile almost all of what you need to build a trading algorithm from start to finish in this one article. Hope this helps!