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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python, (Paperback)
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This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.
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Hvad der skiller sig ud
Comprehensive Coverage
This book offers extensive insights into both machine learning and deep learning using Python, equipping readers with the knowledge to tackle a wide range of AI problems effectively.
Hands-On Projects
With practical examples and projects, readers can apply concepts immediately, enhancing understanding and real-world application of machine learning and deep learning techniques.
Expert Guidance
Authored by experienced professionals, the book provides expert tips and best practices, ensuring readers learn the most efficient methods for using PyTorch and Scikit-Learn in their projects.
Produktdetaljer
- This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch s simple to code framework.Purchase of the print or Kindle book includes a free eBook in PDF format.Key Features: - Learn applied machine learning with a solid foundation in theory- Clear, intuitive explanations take you deep into the theory and practice of Python machine learning- Fully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practicesBook Description: Machine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself.Why PyTorch?PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric.You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP).This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What You Will Learn: - Explore frameworks, models, and techniques for machines to learn from data- Use scikit-learn for machine learning and PyTorch for deep learning- Train machine learning classifiers on images, text, and more- Build and train neural networks, transformers, and boosting algorithms- Discover best practices for evaluating and tuning models- Predict continuous target outcomes using regression analysis- Dig deeper into textual and social media data using sentiment analysisWho this book is for: If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch.Before you get started with this book, you'll need a good understanding of calculus, as well as linear algebra.
| Publication date | February, 2022 |
| Author | Packt Publishing |
| Book format | Paperback |
| Genre | Textbooks |
| Pages | 774 |
| Age group | Adult |
| Series title | No Series |
| Fiction/nonfiction | Non-Fiction |
| Publisher | Packt Publishing |
| Educational level | General |
| Subgenre | General |
| Original languages | English |
| Edu focus | Mathematics |
| Digital audio file format | |
| Digital file format | |
| Is collectible | N |
| Bisac subject heading | Mathematics |
| Edition | 1 |
| Digital reader format | |
| Language | English |
| Pub date | 2022-02-25 |
| Item Weight | 2 lbs (910 grams) |
Hvem bør købe?
-
Beginners in ML
Ideal for newcomers seeking a comprehensive guide to machine learning concepts and Python application using PyTorch and Scikit-Learn.
-
Data Scientists
Useful for data professionals wanting to enhance their skills in practical machine learning and deep learning model development.
-
Educators
Perfect for teachers looking for structured resources to introduce machine learning topics in their curriculum effectively.
-
Advanced Users
May not suit experienced practitioners seeking advanced theory or cutting-edge techniques beyond introductory material.
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Sebastian Raschka All Books Editorial Review
Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python, (Paperback) is an insightful textbook published by Packt Publishing, designed for those eager to delve into the realms of machine learning and deep learning. Spanning 774 pages, this non-fiction book not only covers essential concepts but also offers hands-on projects to enhance practical skills. Whether you're a student or a professional looking to master the intricacies of algorithms, it serves as an invaluable resource. The book is written in clear English, making it accessible to a broad audience interested in advancing their knowledge in mathematics and programming.
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- Rich content on machine learning concepts
- Hands-on projects for practical learning
- Suitable for both beginners and professionals
- Covers deep learning techniques effectively
- Well-organized material for easy understanding
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- Paperback format may be less durable than hard copies
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Egenskaber og fordele
- Comprehensive guide to machine learning and deep learning with PyTorch.
- Learn both theory and application with clear, intuitive explanations.
- Fully updated to cover advanced topics like GANs, graph neural networks, and transformers.
- Includes practical tutorials and best practices for building machine learning systems.
- Perfect for Python developers wanting to start or deepen their machine learning journey.
- Free eBook included with purchase.
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