About ML Notebook
ML Notebook aims to make machine learning concepts accessible through interactive visualizations and clear explanations. We believe that understanding the fundamentals of machine learning algorithms is essential for anyone interested in the field.
Our interactive approach allows you to see how different algorithms work with various parameters and datasets, providing intuitive insights into their behavior without requiring complex mathematical understanding or programming knowledge.
- Interactive visualizations for various machine learning algorithms
- Comprehensive explanations of algorithm mechanics
- Adjustable parameters to see how algorithms respond to different settings
- Comparison tools to understand differences between similar models
- Curated learning resources and glossary of terms
- Mobile-friendly interface for learning on the go
Navigate through the different sections using the main menu. Each algorithm page contains:
- Overview: A high-level explanation of the algorithm
- Interactive Demo: Visualizations that let you experiment with the algorithm
- Mathematical Foundation: The underlying equations and principles
- Applications: Real-world use cases and examples
Explore models that learn from labeled data to make predictions on new, unseen data.
Discover algorithms that find patterns and structures in unlabeled data.
Learn about deep learning models inspired by the structure of the human brain.
Ready to explore machine learning algorithms? Start by browsing our collection of models or check out the learning resources for a structured approach.