Description
Machine learning, the force behind self-driving cars, intuitive personal assistants, intelligent product recommendations, human-like robots, and the seamless magic of web searches, is not just a subject of academic curiosity; it is the very heartbeat of innovation in our society. It is the engine driving unprecedented progress, redefining industries, and, quite literally, shaping the way we experience the world.
Artificial Neural Networks - A Beginner's Guide provides a detailed look at the inner workings of deep neural networks, additional classes of neural networks, and optimization techniques through rigorous mathematical analysis and implementation examples in Python. This book is appropriate for those wanting to know the "how and why" behind neural networks and those interested in learning how to implement a fully functional, from-scratch deep neural network framework.