The second book in the Deep Learning with Python series is here and is primed to give you a deeper insight into deep learning and its topics.
While the first book established the basics, this book will explore them in greater depth to give you a far better understanding with practical examples and real world applications.
Inside you will learn all about:
Using scikit/learn to implement regression modelsEvaluating models and going beyond linear regressionDNNs, RNN, CNNs and their attendant functionalitiesPyTorch and using it for deep learning- tensors, autograd, nn moduleLSTMs and using them in practical waysand much more
Grab your copy today