jcasasr/Libro-Deep-Learning
Material adicional del libro "Deep Learning: Principios y fundamentos", publicado por la Editorial UOC
This provides practical coding exercises that reinforce the concepts taught in the book "Deep Learning: Principles and Fundamentals." It takes theoretical knowledge about neural networks and autoencoders and translates it into hands-on Jupyter Notebook examples. This is for students, academics, or professionals studying deep learning who want to apply what they've learned in a practical coding environment.
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Use this if you are reading "Deep Learning: Principios y fundamentos" and want to immediately practice implementing the concepts from each chapter with provided code examples.
Not ideal if you are looking for a standalone deep learning course or a reference guide that does not require the companion textbook.
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Language
Jupyter Notebook
License
GPL-3.0
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Last pushed
Mar 06, 2023
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