Python Machine Learning By Example: Unlock machine learning best practices with real-world use cases, Edition 4

• 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
• Purchase of the print or Kindle book includes a free PDF copy

• Follow machine learning best practices throughout data preparation and model development
• Build and improve image classifiers using convolutional neural networks (CNNs) and transfer learning
• Develop and fine-tune neural networks using TensorFlow and PyTorch
• Analyze sequence data and make predictions using recurrent neural networks (RNNs), transformers, and CLIP
• Build classifiers using support vector machines (SVMs) and boost performance with PCA
• Avoid overfitting using regularization, feature selection, and more

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.