Predict Bitcoin Prices With Machine Learning And Python [W/Full Code]

We'll predict the future price of Bitcoin using historical price and sentiment data. We'll use data on the USD/BTC price from Yahoo Finance, along with data from Wikipedia about edits to the Bitcoin page.

We'll merge and combine this data, then use it to train a random forest model that will tell us if Bitcoin prices will increase or decrease tomorrow. We'll then switch to an XGBoost model and better predictors to improve accuracy.

We'll develop a backtesting system and use a robust error metric so we can tell if the algorithm is performing well. This system will also be able to make next-day predictions.

This project can be extended to other cryptocurrencies, or be used to predict multiple days ahead.

You can find the full code and README here - https://github.com/dataquestio/projec... .

Chapters

0:00 Project overview
02:33 Downloading edits from Wikipedia
04:57 Finding the sentiment of page edits
14:17 Converting sentiment data into a DataFrame
19:32 Downloading Bitcoin price data
23:49 Preparing data for machine learning
27:38 Training our baseline ML model
32:07 Evaluating error with backtesting
37:05 Using an XGBoost model
39:12 Improving precision with trends
46:03 Generating future predictions
46:56 Next steps to improve the model

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