Deep Learning with Python is a comprehensive guide to building and training deep neural networks using Python and popular deep learning frameworks. Whether you are a beginner or an experienced data scientist, this book provides a detailed understanding of the theory and practical implementation of deep learning.
Starting with an introduction to deep learning, the book covers essential topics such as neural network architecture, training and optimization, regularization, and transfer learning. It also covers popular deep learning frameworks such as TensorFlow, Keras, and PyTorch.
The book includes practical examples and step-by-step instructions to help you build and train deep neural networks for a variety of applications, including image and speech recognition, natural language processing, and time series analysis. You will also learn how to use advanced techniques such as convolutional neural networks, recurrent neural networks, and generative adversarial networks.
With its comprehensive coverage of deep learning and practical examples, this book is an essential resource for anyone interested in building and training deep neural networks using Python and popular deep learning frameworks.
