Deep Learning: Python for Data Science: A Guide to using Python for Tensor Flow, PyTorch, Keras in creating Deep Learning Model Frameworks
Deep Learning: Python for Data Science: A Guide to using Python for Tensor Flow, PyTorch, Keras in creating Deep Learning Model Frameworks
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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
Deep Learning: Python for Data Science: A Guide to using Python for Tensor Flow, PyTorch, Keras in creating Deep Learning Model Frameworks
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
Numéro d'article: 141578022

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

Numéro d'article: 141578022

XOF 38525

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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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Ce qui se démarque

Comprehensive Python Guide
Offers an extensive overview of using Python tools like TensorFlow, PyTorch, and Keras, catering to data science enthusiasts looking to deepen their understanding of deep learning frameworks.
Practical Frameworks
Focuses on hands-on projects that demonstrate the creation and deployment of deep learning models, empowering users to apply theoretical knowledge in practical scenarios.
User-Friendly Approach
Designed for beginners and experienced developers alike, it simplifies complex concepts and encourages self-paced learning, making deep learning accessible to a broader audience.

Détails du produit

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  • 8 x 10 Inch Large Pages - Color VersionDeep Learning: Python for Data Science A Guide to Using Python for TensorFlow, PyTorch, and Keras in Creating Deep Learning Model FrameworksUnlock 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—TensorFlow, PyTorch, and Keras. Whether you’re an aspiring data scientist, experienced developer, or technology enthusiast, this book provides a hands-on approach to mastering deep learning techniques crucial for today’s AI-driven world.Inside This Book:Foundations of Deep Learning: Understand neural networks, their evolution from traditional machine learning, and their applications in image recognition, natural language processing, and recommendation systems.Mastering TensorFlow: Dive into TensorFlow’s execution models, tensor operations, and data pipelines. Learn to build and optimize models, leverage GPU support, and enhance performance with tf.function.Harnessing Keras for Simplicity and Power: Utilize Keras to streamline model development. From Sequential models for quick prototypes to the Functional API for complex architectures, gain skills in compiling, training, evaluating, and visualizing models with TensorBoard.Exploring PyTorch’s Flexibility: Transition to PyTorch’s dynamic computation graph and intuitive design. Master tensor operations, define models with torch.nn.Module, implement automatic differentiation, and develop robust training scripts.Advanced Model Architectures: Enhance your models with multi-input/multi-output architectures, custom layers, and modules. Optimize training workflows with data augmentation, normalization, dropout, and batch normalization.Data Preprocessing and Input Pipelines: Effectively handle diverse data types—images, text, and tabular data. Convert raw data into tensors, utilize tf.data and torch.utils.data.Dataset for efficient data handling, and implement strategies for large-scale datasets.Deployment and Serving Models: Transition models to production with TensorFlow Serving and TorchServe. Create REST APIs using Flask or FastAPI, design batch inference pipelines, and optimize infrastructure for low latency and high throughput.For those interested in:zdeep learning, Python for data science, TensorFlow, PyTorch, Keras, neural networks, machine learning, AI models, data preprocessing, model training, model deployment, deep learning frameworks, advanced deep learning, data science guide, practical deep learning, building AI models, training neural networks, deploying deep learning models, TensorFlow tutorials, PyTorch tutorials, Keras tutorials, machine learning with Python, AI development, deep learning applications, image recognition, natural language processing, recommendation systems, GPU acceleration, TensorFlow vs PyTorch, Keras models, deep learning techniques, data science workflows, automated machine learning, deep learning projects, scalable AI models, deep learning optimization, model evaluation, deep learning pipelines, real-world AI, responsible AI, ethical deep learning, deep learning best practices, hands-on deep learning, comprehensive deep learning, multi-framework deep learning, deep learning strategies
Publisher Independently published
Publication date May 19, 2025
Language English
Print length 125 pages
ISBN-13 979-8284474990
Item Weight 13.4 ounces (379.89 grams)
Dimensions 8.25 x 0.49 x 11 inches (21 x 1.2 x 27.9 cm)

À qui est-ce destiné ?

Suitable For
  • Beginner Data Scientists

    Ideal for novices seeking to understand deep learning concepts and Python frameworks step-by-step.

  • Machine Learning Enthusiasts

    Great for those wanting to enhance their skills in deep learning with practical Python applications.

  • Developers Transitioning

    Helpful for software developers looking to transition into data science and deep learning environments.

Not Suitable For
  • Advanced Practitioners

    Not suitable for experienced deep learning professionals seeking high-level or cutting-edge research topics.

  • Casual Learners

    May not meet the needs of individuals seeking casual, non-technical deep learning overviews.

  • Non-Programmers

    Not recommended for those without programming knowledge, as the book requires Python understanding for effective learning.

DESCRIPTION DU PRODUIT

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Questions et réponses des clients

  • question: What frameworks does the book cover?

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

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

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

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XOF 38525

Commandez maintenant et recevez votre commande aux alentours du Samedi, Juillet 04

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Ubuy s'engage à protéger votre sécurité et votre confidentialité. Notre système avancé de sécurité des paiements garantit la confidentialité en chiffrant vos informations lors de la transmission grâce aux protocoles AES (Advanced Encryption Standards) et SSL (Secure Socket Layer). Vos coordonnées de paiement sont 100 % sécurisées car nous ne partageons pas vos informations de paiement avec des vendeurs tiers.

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Caractéristiques et avantages

  • 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.