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Python Machine Learning - Second Edition: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow
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Python Machine Learning - Second Edition: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow
Python Machine Learning - Second Edition: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow
Artigo n.º: 7635112

Python Machine Learning - Second Edition: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow

Artigo n.º: 7635112

STD 929590

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O que se Destaca

Comprehensive Guide
This edition offers in-depth coverage of both machine learning and deep learning techniques, providing readers with tools necessary to implement complex algorithms effectively.
Practical Applications
Focuses on real-world examples using Python, Scikit-learn, and TensorFlow, making theoretical concepts relatable and easy to understand for learners at all levels.
Updated Content
Includes the latest advancements in machine learning technology and best practices, ensuring readers are equipped with contemporary knowledge and skills for today's data-driven landscape.

Detalhes do produto

Explore the world of Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow. Get the 2nd edition now at Ubuy São Tomé and Príncipe.
  • Second edition of the bestselling book on machine learning now updated for 2020
  • Practical approach to key frameworks in data science, machine learning, and deep learning using Python
  • Introduction to deep learning using TensorFlow and three new chapters focusing on deep learning applications
  • Insight and expertise on machine learning and deep learning algorithms
  • Includes popular libraries like TensorFlow 1.x, scikit-learn v0.18.1, and Keras neural network library
  • Balanced mix of theory and practical examples, providing inspiration for applying fundamental techniques
Item Weight2 lbs (910 grams)

Quem Deverá Comprar?

Suitable For
  • Aspiring Data Scientists

    Perfect for beginners who aim to build foundational machine learning skills using Python and popular libraries.

  • Seasoned Developers

    Great for experienced programmers looking to expand their expertise into machine learning and deep learning.

  • Academic Researchers

    Useful for students and researchers who need a practical guide to machine learning concepts and implementations.

Not Suitable For
  • Absolute Beginners

    Not suitable for those with no programming experience, as prior knowledge of Python is assumed.

  • Casual Learners

    Less ideal for individuals looking for a light introduction to machine learning without diving deep.

  • Non-technical Managers

    May not benefit those in management roles who seek high-level insights rather than technical details.

DESCRIÇÃO DO PRODUTO

Python Machine Learning - Second Edition: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow

About This Item

Looking to delve into the world of Machine Learning and Deep Learning with Python? Look no further than the "Python Machine Learning - Second Edition: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2nd Edition." This comprehensive guide is perfect for anyone interested in honing their skills in the field of Python Machine Learning. With a focus on implementing practical applications, this book provides insights on how to leverage the power of scikit-learn and TensorFlow to build advanced Machine Learning models. Whether you're an e-commerce professional or a data enthusiast looking to optimize your e-commerce platform, this book offers a wealth of knowledge and techniques specifically tailored to the e-commerce industry. Learn how to apply Python Machine Learning techniques to enhance business strategies, optimize e-commerce platforms, and develop cutting-edge prediction models. Scikit-learn, a popular Python library for Machine Learning, is explored in detail.

Discover how to analyze e-commerce data, implement data analysis techniques, and apply scikit-learn algorithms to gain valuable insights. From data preprocessing to model selection, this book covers all aspects of using scikit-learn in e-commerce optimization. Furthermore, "Python Machine Learning - Second Edition" also explores the potential of TensorFlow in developing powerful Machine Learning models for e-commerce recommendation systems. Dive into the world of Deep Learning with Python and learn how to build and train neural networks to deliver accurate predictions and improve customer experiences. By combining the power of Python, scikit-learn, and TensorFlow, this book equips you with the tools and knowledge needed to make data-driven decisions and stay ahead in the competitive e-commerce landscape.

Take advantage of Machine Learning and Deep Learning algorithms to unlock new business opportunities, streamline operations, and boost profitability. Don't miss out on the opportunity to enhance your e-commerce business with the latest advancements in Python Machine Learning. Get your copy of "Python Machine Learning - Second Edition" now and embark on a journey towards becoming a proficient Machine Learning specialist in the e-commerce industry.

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Perguntas e Respostas dos Clientes

  • pergunta: What topics are covered in Python Machine Learning - Second Edition?

    Resposta: The book covers a comprehensive range of topics including the fundamentals of machine learning, deep learning techniques, and practical applications of Python with libraries like scikit-learn and TensorFlow. You'll learn about supervised and unsupervised learning, model evaluation, neural networks, and more. This edition includes real-world examples to demonstrate how these concepts are applied in fields such as healthcare and finance, making it ideal for both beginners and experienced practitioners.
  • pergunta: Is this book suitable for beginners in machine learning?

    Resposta: Yes, 'Python Machine Learning - Second Edition' is suitable for beginners. It starts with foundational concepts before progressing to advanced topics, making it accessible for those new to the field. The author uses clear explanations and practical examples to ensure that even those without prior experience can grasp complex ideas, paving the way for readers to confidently implement machine learning solutions in various projects.
  • pergunta: What programming experience do I need to read this book?

    Resposta: While a basic understanding of programming, especially in Python, is helpful, it is not strictly necessary. The book assumes some prior knowledge of Python syntax and programming concepts but does provide a gentle introduction to key elements needed for machine learning. Readers can benefit from practicing Python alongside the book’s examples, which facilitates a smoother learning experience.
  • pergunta: Are there practical projects included in this edition?

    Resposta: Yes, the second edition includes multiple hands-on projects that allow readers to apply machine learning concepts in real-world scenarios. These projects cover various industries, providing insight into how machine learning can solve specific problems. By working through these practical applications, readers will enhance their understanding of the material and gain valuable experience.
  • pergunta: Can this book help me prepare for a job in data science?

    Resposta: Absolutely! This book provides a solid foundation in machine learning that is vital for a career in data science. By mastering the techniques and concepts illustrated in the book, readers will be well-equipped to tackle machine learning tasks commonly encountered in industry roles. Moreover, practical case studies can bolster your portfolio when entering the job market.
  • pergunta: What is the difference between machine learning and deep learning explained in the book?

    Resposta: The book differentiates between machine learning and deep learning by illustrating their distinct methods. Machine learning typically involves algorithms that learn from data, while deep learning uses neural networks and is particularly effective for complex tasks like image and speech recognition. By understanding these differences, readers can choose the appropriate approach for their specific data problems.
  • pergunta: Are updates or additional resources provided with the book?

    Resposta: Yes, the author often provides supplementary materials and updates on a dedicated website or LinkedIn page. These resources may include code examples, datasets, or even tutorials that complement the reading experience. Accessing these materials can enhance understanding and keep readers informed on the latest trends and techniques in machine learning.
  • pergunta: What makes this second edition different from the first?

    Resposta: This second edition offers updated content, incorporating new algorithms and techniques that have emerged in the rapidly evolving field of machine learning. It includes more examples and exercises based on contemporary industry practices, ensuring that the material remains relevant and up to date. This responsiveness to recent developments makes it a valuable resource for learners.
  • pergunta: What prerequisites should I be aware of before starting this book?

    Resposta: Before starting 'Python Machine Learning - Second Edition,' it's beneficial to have a basic understanding of Python programming and high school-level mathematics, particularly in statistics and linear algebra. While the book provides introductory explanations for essential concepts, prior knowledge will help you grasp technical details and execute the coding examples more effectively.
  • pergunta: Where can I buy Python Machine Learning - Second Edition in São Tomé and Príncipe?

    Resposta: You can purchase 'Python Machine Learning - Second Edition' conveniently from Ubuy in São Tomé and Príncipe. Ubuy offers a user-friendly online shopping experience, along with a range of shipping and payment options tailored for Zambian customers. This ensures that you can easily acquire this essential resource for mastering machine learning.

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STD 929590

Encomende já e receba por volta de Quarta-feira, Julho 08

QTY:

Transação seguraTransação segura

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