This repository explores the application of machine learning techniques in the domain of finance. From credit score predictions to financial product recommendations, dive into various notebooks that demonstrate the power of ML in the financial sector.
- Credit Score Prediction
- DBSCAN Fundamental Analyses
- Fraud Detection
- PCA for Trading Strategies
- Financial Product Recommendation
- Installation and Setup
- Contributing
- License
Explore the "Credit score.ipynb" notebook to understand how machine learning can be used to predict or analyze credit scores.
The "Main.ipynb" notebook in this section discusses the application of the DBSCAN clustering algorithm for fundamental analyses in finance.
Dive into the "fraud_detect.ipynb" notebook to learn about detecting fraudulent activities in banking or financial transactions using machine learning techniques.
The "PCA_for_stock_portfolio.ipynb" notebook showcases the application of Principal Component Analysis (PCA) for stock portfolio management or trading strategies.
Discover how machine learning can be used to build recommendation systems for financial products in the "recommendation engine.ipynb" notebook.
git clone https://github.com/amaboh/Machine_learning_in_finance.git
cd Machine_learning_in_finance
# Follow specific setup instructions for each notebook
This project is licensed under the MIT License. See the LICENSE.md file for details.