yandexdataschool/Practical_DL

What it solves

This repository provides a structured curriculum for learning deep learning, helping students transition from basic concepts to building and training neural networks using modern frameworks.

How it works

The course is organized into weekly modules, each containing lecture materials and practical seminars. Students can complete assignments either on their local machines or via Google Colab. The curriculum covers foundational topics like backpropagation and optimization, moving into practical implementation with PyTorch, and exploring specific architectures like Convolutional Neural Networks (CNNs).

Who it’s for

This project is designed for students enrolled in the Deep Learning course at Yandex Data School. It is suitable for anyone looking for a guided, hands-on approach to mastering deep learning techniques through structured weekly lessons and coding exercises.

Highlights

• Weekly lecture and seminar materials covering core deep learning concepts.
• Hands-on assignments designed for local or Google Colab environments.
• Practical focus on PyTorch and neural network implementation.
• Collaborative development with contributions from researchers and students.