Create a fully connected feedforward neural network from the ground up with Python — unlock the power of deep learning!

By the end of the book, you’ll pack everything into a complete Python deep learning library, creating your own class hierarchy of layers, activation functions, and neural network architectures ...

Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases.

Discover the best deep learning software for training and deploying neural networks with powerful features and customizable options.

Both libraries provide high-level APIs for building and training neural networks, making it easy for developers to get started. What are some popular deep learning libraries for Python?

Curious about this strange new breed of AI called an artificial neural network? We've got all the info you need right here.

This collection welcomes submissions on explainability techniques for deep learning neural networks, encompassing diverse neural architectures and ensuring broad applicability to different domains.

By the end of the course, students will confidently apply their knowledge to build powerful Deep Neural Networks using PyTorch and Python libraries for various machine learning applications.