Finance ML Lab

A clean Python environment for financial machine learning research and analysis.

Setup Instructions

Prerequisites

• Python 3.11 or higher
• pip (Python package installer)

Installation

1. Create a virtual environment (recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts�ctivate

2. Install dependencies:

   pip install -r requirements.txt

3. Start Jupyter Notebook:

   jupyter notebook

Included Libraries

• Data Science: numpy, pandas, matplotlib, scikit-learn, statsmodels
• Financial Data: yfinance
• Deep Learning: torch
• Visualization: seaborn, plotly
• Scientific Computing: scipy
• Development: jupyter, notebook

Project Structure

finance-ml-lab/
├── datasets/          # Store your datasets here
├── notes/            # Research notes and documentation
├── projects/         # Individual ML projects
├── requirements.txt  # Python dependencies
└── README.md        # This file

Getting Started

1. Navigate to the projects/ directory
2. Create a new Jupyter notebook for your analysis
3. Import the libraries you need and start exploring!

Example Usage

import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt

# Download stock data
data = yf.download('AAPL', start='2020-01-01', end='2023-01-01')
print(data.head())