LastAncientOne/Deep_Learning_Machine_Learning_Stock resource

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1785 stars · 365 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Jupyter Notebook tutorials and studies applying machine learning and deep learning algorithms to stock price prediction. It covers feature engineering, technical and fundamental analysis, and both long-term and short-term trading strategies.

Use cases

• predict stock prices with machine learning
• learn deep learning for stock trading
• feature engineering for financial data
• apply neural networks to stock market data
• study technical analysis with Python
• build stock prediction models in Jupyter notebooks

When to choose

• you want educational notebooks on ML/DL applied to stock prediction
• you are learning feature engineering and selection for financial time series
• you want to experiment with different algorithms on stock data

When to avoid

• you need production-ready trading software or a backtesting framework
• you expect guaranteed profitable trading signals
• you need maintained, tested library code rather than study notebooks

Facets

learning-resource · maturity active

machine-learning deep-learning data-science trading fintech machine-learning data-science python cross-platform stock-prediction jupyter-notebooks technical-analysis feature-engineering financial-machine-learning educational trading

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