This book is for engineers, data analysts, and data scientists, interested in deep learning, and those looking to explore and implement advanced algorithms with PyTorch. Knowledge of machine learning is helpful but not mandatory. Knowledge of Python programming is expected.
- Title Page
- Copyright and Credits
- Dedication
- Packt Upsell
- Foreword
- Contributors
- Preface
- Getting Started with Deep Learning Using PyTorch
- Building Blocks of Neural Networks
- Diving Deep into Neural Networks
- Fundamentals of Machine Learning
- Deep Learning for Computer Vision
- Deep Learning with Sequence Data and Text
- Generative Networks
- Neural style transfer 
- Generative adversarial networks
- Deep convolutional GAN
- Language modeling 
- Summary
- Modern Network Architectures
- What Next?
- Other Books You May Enjoy
Who this book is for
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