Deep Learning: Python for Data Science: A Guide to using Python for Tensor Flow, PyTorch, Keras in creating Deep Learning Model Frameworks Hardcover – 19 May 2025
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Deep Learning: Python for Data Science: A Guide to using Python for Tensor Flow, PyTorch, Keras in creating Deep Learning Model Frameworks Hardcover – 19 May 2025
Unlock the transformative power of deep learning with Deep Learning: Python for Data Science, your essential guide to building, training, and deploying advanced deep learning models using Python’s leading frameworks.
Deep Learning: Python for Data Science: A Guide to using Python for Tensor Flow, PyTorch, Keras in creating Deep Learning Model Frameworks Hardcover – 19 May 2025
Articolo #: 138662018

Deep Learning: Python for Data Science: A Guide to using Python for Tensor Flow, PyTorch, Keras in creating Deep Learning Model Frameworks Hardcover

Articolo #: 138662018

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Unlock the transformative power of deep learning with Deep Learning: Python for Data Science, your essential guide to building, training, and deploying advanced deep learning models using Python’s leading frameworks.
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Cosa salta all'occhio

Cobertura Integral
This guide offers in-depth insights into using Python with TensorFlow, PyTorch, and Keras, ensuring learners grasp deep learning frameworks effectively.
User-Friendly Approach
Designed for both beginners and advanced users, it simplifies complex concepts, making deep learning accessible to everyone wanting to harness Python.
Aplicaciones prácticas
Includes hands-on projects and examples, allowing readers to immediately apply their knowledge and build real-world deep learning models.

Dettagli del prodotto

Shop Deep Learning: Python for Data Science: A Guide to using Python for Tensor Flow, PyTorch, Keras in creating Deep Learning Model Frameworks Hardcover – 19 May 2025 online at a best price in San Marino. B0F993LDJL
Peso del artículo2 lbs (910 gramos)

A chi è consigliato?

Suitable For
  • Aspiring Data Scientists

    Provides essential knowledge and skills needed for anyone looking to enter the field of data science.

  • Machine Learning Enthusiasts

    Perfect for individuals who wish to deepen their understanding of deep learning frameworks and methods using Python.

  • Tech Educators

    Useful for instructors looking to update curricula with current deep learning framework practices and implementations.

Not Suitable For
  • Complete Beginners

    Not suitable for those without prior programming or data science knowledge, as it assumes foundational skills.

  • Lectores Casual

    Individuals not seriously interested in deep learning may find the content too technical and dense.

  • Non-Technical Professionals

    Professionals outside tech fields might struggle with the technical jargon and concepts presented throughout the book.

DESCRIZIONE DEL PRODOTTO

Deep Learning: Python for Data Science: A Guide to using Python for Tensor Flow, PyTorch, Keras in creating Deep Learning Model Frameworks Hardcover – 19 May 2025

Hai qualche domanda? chatta con noi

Domande e risposte dei clienti

  • domanda: What frameworks does the book cover?

    Rispondere: The book covers TensorFlow, PyTorch, and Keras.
  • domanda: Is this book suitable for beginners?

    Rispondere: Yes, it is suitable for both beginners and experienced developers.
  • domanda: What can I expect to learn from this book?

    Rispondere: You will learn to build, train, and deploy advanced deep learning models.

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€ 89

Ordina subito e indossalo Sunday, Giugno 28

QTY:

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Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.

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Caratteristiche e benefici

  • Comprehensive guide to deep learning using Python.
  • Covers TensorFlow, PyTorch, and Keras frameworks.
  • Ideal for aspiring data scientists and experienced developers.
  • Hands-on approach for building and deploying models.
  • Includes advanced techniques for model architectures and data preprocessing.
  • Offers practical insights for transitioning models into production.