Tensorflow 2.0: Deep Learning and Artificial Intelligence

Tensorflow 2.0: Deep Learning and Artificial Intelligence

Welcome to Tensorflow 2.0!


What an exciting time. It's been nearly 4 years since Tensorflow was released, and the library has evolved to its official second version.

Tensorflow is Google's library for deep learning and artificial intelligence.

Deep Learning has been responsible for some amazing achievements recently, such as:

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Generating beautiful, photo-realistic images of people and things that never existed (GANs)



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Beating world champions in the strategy game Go, and complex video games like CS:GO and Dota 2 (Deep Reinforcement Learning)



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Self-driving cars (Computer Vision)



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Speech recognition (e.g. Siri) and machine translation (Natural Language Processing)



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Even creating videos of people doing and saying things they never did (DeepFakes - a potentially nefarious application of deep learning)



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Natural Language Processing (NLP)



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Recommender Systems



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Transfer Learning for Computer Vision



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Generative Adversarial Networks (GANs)



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Deep Reinforcement Learning Stock Trading Bot



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Deploying a model with Tensorflow Serving (Tensorflow in the cloud)



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Deploying a model with Tensorflow Lite (mobile and embedded applications)



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Distributed Tensorflow training with Distribution Strategies



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Writing your own custom Tensorflow model



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Converting Tensorflow 1.x code to Tensorflow 2.0



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Constants, Variables, and Tensors



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Eager execution



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Gradient tape



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Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)


https://bit.ly/3EGn3IC

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