This repo contains study materials for course on machine and deep learning using batchflow framework.
- Presentations folder contains pdfs with slides for presentations.
- Tutorials folder contains interactive ml and dl demos (find even more here!).
- Demo folder contains demos from real business cases.
Batchflow itself is embedded into repo as a git submodule.
Note, that all materials here are not self-sufficient and mean to act as auxiliary tool when teaching data science concepts.
- Introduction to statistical learning: main ML concepts with minimal mathematical explanations. Focused on classical models (linear models, kNN, trees, forests and so on). Great choice for a first book.
- Deep learning: excellent first part includes math basics of ML. The rest of the book is a strong explanation of neural networks.
- Глубокое обучение: погружение в мир нейронных сетей.
We also can advice you a great Stanford University course CS231n: Convolutional Neural Networks for Visual Recognition, containing both detailed lecture slides and repo with assignments.