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Introduction to Deep Learning and Neural Networks with Python(TM)
ISBN-13:
9780323909341
Veröffentl:
2020
Seiten:
300
Autor:
Ahmed Fawzy Gad
eBook Typ:
EPUB
eBook Format:
EPUB
Kopierschutz:
2 - DRM Adobe
Sprache:
Englisch
Beschreibung:
Introduction to Deep Learning and Neural Networks with Python(TM): A Practical Guide is an intensive step-by-step guide for neuroscientists to fully understand, practice, and build neural networks. Providing math and Python(TM) code examples to clarify neural network calculations, by book's end readers will fully understand how neural networks work starting from the simplest model Y=X and building from scratch. Details and explanations are provided on how a generic gradient descent algorithm works based on mathematical and Python(TM) examples, teaching you how to use the gradient descent algorithm to manually perform all calculations in both the forward and backward passes of training a neural network.
1. Preparing the Development Environment2. Introduction to ANN3. ANN with 1 Input and 1 Output4. Working with Any Number of Inputs5. Working with Hidden Layers6. Using Any Number of Hidden Neurons7. ANN with 2 Hidden Layers8. ANN with 3 Hidden Layers9. Any Number of Hidden Layers10. Generic ANN11. Speeding Neural Network using Cython and PyPy12. Deploying Neural Network to Mobile Devices
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