Welcome to the Deep Learning documentation section! 📚🧠 This guide provides essential resources and recommendations for exploring deep learning concepts, frameworks, and applications.

Recommended Books

Here are some foundational texts for beginners and experts alike:

  • "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
    A comprehensive overview of neural networks and modern machine learning techniques.

    Deep_Learning
    [Read more about this book](/Documentation/en/Books/MachineLearning)

  • "Neural Networks and Deep Learning" by Michael Nielsen
    A beginner-friendly introduction with interactive examples.

    Neural_Networks_and_Deeplearning
    [Explore the full tutorial](/Documentation/en/Tutorials/DeepLearning)

  • "Deep Learning for Coders" by fast.ai
    Practical coding-focused lessons for hands-on learning.

    Deep_Learning_for_Coders
    [Check out the course](/Documentation/en/Courses/DeepLearning)

Key Concepts & Resources

  • Neural Networks: Understand the basics of layers, activation functions, and backpropagation.

    Neural_Network_Structure

  • Frameworks: Dive into popular tools like TensorFlow and PyTorch.

    TensorFlow_PyTorch_Comparison
    [Learn more about TensorFlow](/Documentation/en/Tools/TensorFlow) | [Explore PyTorch documentation](/Documentation/en/Tools/PyTorch)

  • Applications: Discover how deep learning is used in computer vision, NLP, and reinforcement learning.

    Deep_Learning_Applications

For advanced topics, check our Deep Learning Research section! 📈🔍