Resources¶

Curated collections of books, courses, tools, and references across multiple programming languages and technical domains.

💻 Programming¶

Comprehensive resources for multiple programming languages.

Python ¶

Python fundamentals, advanced topics, and key libraries for data science and ML.

R ¶

R programming, Tidyverse ecosystem, and statistical packages.

Rust ¶

Rust fundamentals and ML tools for performance-critical systems.

JavaScript ¶

Modern JavaScript and TypeScript for web development.

Java ¶

Java enterprise systems and backend development.

Note

Other programming languages will be added as we progress developing this site.

Data Science & ML¶

Resources for machine learning, deep learning, and data analysis.

Machine Learning ¶

Supervised, unsupervised, and reinforcement learning methods.

Deep Learning ¶

Neural network frameworks, computer vision, and NLP resources.

Time Series ¶

Time series forecasting, anomaly detection, and temporal analysis.

Featured: ARIMA, Prophet, PyTorch Forecasting, N-BEATS

Statistics ¶

Statistical foundations and Bayesian methods.

Data Engineering ¶

Data pipelines, ETL processes, and database systems.

🛠️ Tools & Platforms¶

Essential development tools and cloud platforms.

Development Tools ¶

Version control, IDEs, and development environments.

Cloud Platforms ¶

AWS, Azure, and GCP resources for ML and data engineering.

Data Visualization ¶

Plotting libraries and visualization tools.

🚀 MLOps & Production¶

Production ML systems, deployment, and monitoring.

Deployment ¶

Docker, Kubernetes, and containerization for ML systems.

Monitoring ¶

Model monitoring, logging, and observability tools.

CI/CD ¶

Continuous integration and deployment pipelines for ML.

🎯 How to Use These Resources¶

For Beginners:
Start with language fundamentals and beginner-friendly courses.

For Practitioners:
Focus on libraries, frameworks, and hands-on tutorials.

For Researchers:
Explore papers, advanced methods, and cutting-edge tools.

For Everyone:
Join communities, practice with real datasets, and build projects.

🤝 Contributing¶

Have a great resource to add?

Email: dr.saad.laouadi@gmail.com
GitHub: Open an issue

Quality over quantity. Resources are curated, not comprehensive. Only proven, high-quality materials make the list.