Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python, (Paperback)
Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python, (Paperback)
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Sebastian Raschka

Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python, (Paperback)

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Key item features

  • Comprehensive Guide: This 774-page paperback, published on 2022-02-25, offers a comprehensive guide to machine learning and deep learning using PyTorch and Scikit-Learn.
  • Key Features: It covers applied machine learning with a strong theoretical foundation, including PyTorch, transformers, XGBoost, and graph neural networks.
  • PyTorch Focus: The book emphasizes PyTorch's ease of use for machine learning, explaining its essential parts and model creation with libraries like PyTorch Lightning and PyTorch Geometric.
  • Advanced Topics: Readers will learn about generative adversarial networks (GANs), reinforcement learning, and the latest deep learning trends such as graph neural networks and large-scale transformers for NLP.
  • Target Audience: Ideal for Python developers and data scientists with a grasp of Python basics, calculus, and linear algebra, seeking to build practical ML and DL applications.
  • Learning Outcomes: Readers will explore frameworks, models, and techniques, train classifiers on various data, build neural networks, and discover best practices for model evaluation and tuning.
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