Predict The Stock Market With Machine Learning And Python

In this tutorial, we'll learn how to predict tomorrow's S&P 500 index price using historical data. We'll also learn how to avoid common issues that make most stock price models overfit in the real world.

We'll start by downloading S&P 500 prices using a package called yfinance. Then, we'll clean up the data with pandas, and get it ready for machine learning.

We'll train a random forest model and make predictions using backtesting. Then, we'll improve the model by adding predictors. We'll end with next steps you can use to improve the model on your own.

Chapters

00:00 - Introduction
01:28 - Downloading S&P 500 price data
03:30 - Cleaning and visualizing our stock market data
04:29 - Setting up our target for machine learning
08:19 - Training an initial machine learning model
17:01 - Building a backtesting system
23:05 - Adding additional predictors to our model
28:45 - Improving our model
33:37 - Summary and next steps with the model

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[superztnt]

Clear and to the point. I hate super long videos full of things that don't provide much value. This one was great. I like that he walked through general data science/machine learning steps. In particular the data cleansing which many skip over, but it is actually an important step. Also, a pet peeve of mine is audio quality. This video you can hear the presenter clearly and he doesn't sound like his is working from a tin can.

[rstea]

I’m new to coding but have always been an avid market watcher and looking for opportunities. Best video I’ve seen since I started scouring the depths of YouTube for this content last week. Thank you sir!

[jackwillison]

I've heard the stock market often does well during election years. I recently inherited a lump sum and want to invest it wisely to take advantage of this potential upswing. Do you have any tips or strategies?

[cooltraderf]

Excellent. This tutorial corrects an error that pretty much every other video from others that I have seen has made. Don't seek MSE precision in your target as your goal. That's not what practitioners are looking for. Do what this educator has done instead. This model gets it right as used in the real world. Solid base to work with. Well done!

[Juoa]

I cannot thank you enough! It's very straight to point and I've learned more in this video than in n online courses and articles.

[edmundobrown]

thank yiu so much fir the video. I have taken varius courses in different places, and your video and teaching style are certainly the best !

[jwia]

This was an amazing walkthrough. I have learned so much!

[logannon]

Great video. Thank you for the insights. Going to be tuning into more of your work.

[emadbagheri]

Searched & watched a LOT of videos. This is the best. Well done man.

[circus]

Vik, I echo the compliments on the excellent video. I was able to use my own bespoke weekly market timing signals aligned with weekly S&P closes to finally get a grounded statistical "opinion" on the predictability of forward returns - as only my second Python exercise! Thanks!

[charlene]

Watched up to 2:26 and I already know this is going to be excellent.
Clear and concise explanation from the start and you know this is going to be more than your ordinary YT tutorial

[tomx]

Excellent video, thank you for sharing this. Hopefully I can see more ML related videos going forward.

[gooddude]

Very thorough and loved it sir. Thanks for the video lesson.

[ricjrob]

Great video. Really clear and at a pace that allowed me to follow it easily and learn some new and simple techniques in how to manipulate data.

[marmadukethurmond]

I've always been interested in binary options, but I never knew where to start. Thanks to you and this video, I finally felt confident enough to give it a try.

[elu]

What a great framework to ML time-series data for prediction. Thanks for sharing!

[Fred-utmc]

Thats a really good video and it seems you really know what you are talking about. Thanks!

[Templar_of_the_Clean_Code]

Very useful man, thanks for show us the way!

[idkidkidk]

This is awesome, instead of showing what you need to learn or try it shows how to actually build a model. This is very usefull. Thank you!

[InvestorLondon]

Incredible video! This helped me a whole lot I really do appreciate it! I Just Liked and Subcribed!