Deep Learning by Code: Build Neural Networks from Scratch, (Paperback)

<p><b>Build Neural Networks from the Ground Up-No Black Boxes, Just Code</b></p><p>If you've ever wanted to truly understand how deep learning works-not just use high-level libraries-<i>Deep Learning by Code</i> is your roadmap.</p><p>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.</p><p>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.</p>Inside You'll Learn: <ul><li><p>How neural networks process information, learn patterns, and make predictions</p></li><li><p>Step-by-step construction of forward and backward propagation</p></li><li><p>Implementing activation functions, loss functions, and optimizers by hand</p></li><li><p>Building feedforward, convolutional, and recurrent neural networks</p></li><li><p>Understanding gradient descent, backpropagation, and weight updates</p></li><li><p>Creating training loops without relying on frameworks</p></li><li><p>Visualizing training behavior and model accuracy</p></li><li><p>Transitioning from raw code to real-world applications</p></li><li><p>Bonus: Compare your custom models to PyTorch and TensorFlow</p></li></ul><p>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 <b>why</b>.</p>

• Deep Learning by Code: Build Neural Networks from Scratch, (Paperback)
• Author: Independently Published
• ISBN: 9798290086538
• Format: Paperback
• Publication Date: 2025-06-28
• Page Count: 240