Key Features
- Discover new and updated content on NLP transformers, PyTorch, and computer vision modeling
- Includes a dedicated chapter on best practices and additional best practice tips throughout the book to improve your ML solutions
- Implement ML models, such as neural networks and linear and logistic regression, from scratch
Who this book is for
This expanded fourth edition is ideal for data scientists, ML engineers, analysts, and students with Python programming knowledge. The real-world examples, best practices, and code prepare anyone undertaking their first serious ML project.