wkambale/python-ds-ai-book

This is a private repository for the ebook "Python for Data Science and AI: An African Perspective" # Python for AI & Data Science: Code Examples This repository contains the complete code examples, snippets, and datasets from the book **"Python for AI & Data Science"**. ## Repository Structure The code is organized by chapter to follow the book's learning path: - **01-toolkit**: Setup and essential tools. - **02-python-fundamentals**: Python core for data science. - **03-sql**: SQL for data analysis using SQLite and BigQuery. - **04-pandas**: Data wrangling and transformation. - **05-data-visualization**: Professional plotting with Matplotlib and Seaborn. - **06-ml-principles**: Machine learning foundations and preprocessing. - **07-classification**: Churn prediction case study. - **08-unsupervised-learning**: Clustering and PCA. - **09-neural-networks**: Introduction to Deep Learning with Keras. - **10-computer-vision**: CNNs and Image Classification. - **11-sequential-data**: RNNs, LSTMs, and Time Series. - **12-transformers**: Modern NLP and Transformer architectures. - **13-llm-apps**: Building applications with Large Language Models. - **14-mlops**: Machine Learning Operations and MLflow. - **15-deployment**: Building and deploying APIs with FastAPI and Docker. - **16-automation-monitoring**: Testing and monitoring models in production. - **17-capstone**: End-to-end data science project. ## How to Use 1. **Clone the repository**: ```bash git clone github.com ``` 2. **Datasets**: The datasets used in the book are available in the `/datasets` directory. 3. **Environments**: It is recommended to use a virtual environment for the projects. Specific requirements are often listed within the code comments. ## African Context Many of these examples utilize African-centric datasets (e.g., MobiCash transactions, agriculture data, local language tokenization) to provide relevant, real-world context for practitioners on the continent.