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Deep Learning by Code: Build Neural Networks from Scratch

by Thompson Carter
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Current price ₹1,661.00
Original price ₹1,844.00
Original price ₹1,844.00
Original price ₹1,844.00
(-10%)
₹1,661.00
Current price ₹1,661.00

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Book cover type: Paperback
  • ISBN13: 9798290086538
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 240
  • Original Price: GBP 14.57
  • Language: English
  • Edition: N/A
  • Item Weight: 327 grams
  • BISAC Subject(s): Languages / Python

Build Neural Networks from the Ground Up-No Black Boxes, Just Code

If you've ever wanted to truly understand how deep learning works-not just use high-level libraries-Deep Learning by Code is your roadmap.

This hands-on guide teaches you how to implement the core building blocks of neural networks from scratch using pure Python and NumPy. You'll code every layer, activation function, and optimization algorithm yourself-gaining a deep, intuitive understanding of how modern AI really works under the hood.

Whether you're a developer, data science student, or aspiring machine learning engineer, this book gives you the confidence and skills to create and experiment with your own deep learning models-line by line.

Inside You'll Learn:
  • How neural networks process information, learn patterns, and make predictions

  • Step-by-step construction of forward and backward propagation

  • Implementing activation functions, loss functions, and optimizers by hand

  • Building feedforward, convolutional, and recurrent neural networks

  • Understanding gradient descent, backpropagation, and weight updates

  • Creating training loops without relying on frameworks

  • Visualizing training behavior and model accuracy

  • Transitioning from raw code to real-world applications

  • Bonus: Compare your custom models to PyTorch and TensorFlow

This isn't just another tutorial-it's a deep dive into the mechanics of deep learning. You'll leave not just knowing how, but why.

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