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Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Python for AI: Deep Learning with TensorFlow and PyTorch

Python for AI: Deep Learning with TensorFlow and PyTorch

Paperback

Series: Python for Ai: Learn Python Programming for Artificial Intelligence, Book 4

General ComputersProgramming

ISBN13: 9798279178858
Publisher: Independently Published
Published: Dec 20 2025
Pages: 366
Weight: 1.87
Height: 0.76 Width: 8.50 Depth: 11.00
Language: English
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.

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Dreisner, Thalric

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Programming