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Python for AI

Deep Learning with TensorFlow and PyTorch

Jazyk AngličtinaAngličtina
Kniha Brožovaná
Kniha Python for AI Thalric Dreisner
Libristo kód: 50642503
Nakladateľstvo Independently published, december 2025
Ever wondered how machines "see," "hear," and "think"? Or why your phone can recognize your face fas... Celý popis
? points 86 b
35.40
Skladom u dodávateľa Odosielame za 9-15 dní

30 dní na vrátenie tovaru

Ever wondered how machines "see," "hear," and "think"? Or why your phone can recognize your face faster than your best friend can spot you at a concert? Welcome to Python for AI: Deep Learning with TensorFlow and PyTorch, the ultimate deep dive into the world where code meets cognition.

This isn't just another dry textbook full of equations and emotionless syntax. This is a guided adventure - part story, part lab, and entirely designed to turn you from an AI enthusiast into a deep learning developer who actually gets it.

I'm Thalric Dreisner, your caffeine-fueled guide through the chaos of neural networks, convolutional layers, and vanishing gradients. Together, we'll explore how machines learn to recognize images, understand text, and even create art - all using the two titans of modern AI: TensorFlow and PyTorch.

What You'll Learn (Without Losing Your Mind)

  • The real difference between machine learning and deep learning (and why it matters).
  • How artificial neurons mimic the human brain to create intelligent systems.
  • Building and training your own neural networks - from scratch and using frameworks.
  • Mastering TensorFlow and PyTorch step-by-step, with hands-on coding examples.
  • Understanding convolutional neural networks (CNNs) for image recognition.
  • Harnessing recurrent neural networks (RNNs) and LSTMs for text and time-series data.
  • Exploring cutting-edge architectures like GANs, Transformers, and Autoencoders.
  • Fine-tuning models with optimizers, regularization, and learning rate scheduling.
  • Managing data pipelines and augmentation for large-scale training.
  • Deploying your trained models to the real world with Flask, FastAPI, and TensorFlow Lite.

Whether you're teaching a model to spot cats, translate poetry, or generate original artwork, this book will make you laugh, think, and (most importantly) build.

Why This Book Stands Out

This is not a book for spectators - it's for builders.

Each chapter blends humor, storytelling, and real-world coding experience so you never feel lost in the math. You'll start with neural fundamentals, master TensorFlow and PyTorch, and end by deploying a working AI model you can show off to your friends, boss, or future robot overlords.

If you've ever looked at an AI paper and thought, "Yeah, no thanks," this book translates that complexity into plain English - with code you can actually run, modify, and expand on.

And if you're following the Mastering Artificial Intelligence with Python series, congratulations - you've reached Book 4, the deep end of the AI pool.

Who This Book Is For
  • Beginners ready to move from machine learning to deep learning.
  • Developers who want to master TensorFlow and PyTorch with confidence.
  • Data scientists looking to strengthen their neural network expertise.
  • Students and self-learners craving a practical, enjoyable guide to AI.
  • Anyone who has ever yelled "Why won't this model converge?" into the void.

You don't need a PhD or a math obsession - just a bit of Python knowledge, curiosity, and a willingness to experiment.

By the End of This Book...

You won't just understand deep learning - you'll speak its language. You'll know why neural networks work, how to debug them, and how to deploy them into real-world systems. Most importantly, you'll have the confidence to keep building, experimenting, and creating.

You'll also see where this journey leads next - to Python for AI: Real-World Projects and Applications, where we turn your deep learning mastery into fully-fledged production AI systems.

So, ready to go deep?

Let's make machines a little smarter - one line of Python at a time.

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