Deep Learning with TensorFlow 2.0 and Keras: Regression, ConvNets, GANs, RNNs, NLP & more with TF 2.0 and the Keras API

This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML.

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Hands On Machine Learning with Scikit Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

This Practical Book Shows You How. By Using Concrete Examples, Minimal Theory, And Two Production-Ready Python Frameworks―Scikit-Learn And Tensorflow―Author Aurélien Géron Helps You Gain An Intuitive Understanding Of The Concepts And Tools For Building Intelligent Systems

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Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn and TensorFlow 2

This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python.

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Deep Learning with Python

If you’ve picked up this book, you’re probably aware of the exưaordinary progress that deep leam ing has represented for the íìeld of artificial intelligence in the recent past. In a mere fĩve years, we’ve gone from near-unusable image recognition and speech transcription, to superhum an períorm ance on these tasks.

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