February 22, 2020

257 words 2 mins read

Zero to ML hero with TensorFlow 2.0

Zero to ML hero with TensorFlow 2.0

Get a programmer's perspective on machine learning with Laurence Moroney, from the basics all the way up to building complex computer vision scenarios using convolutional neural networks and natural language processing with recurrent neural networks.
Talk Title Zero to ML hero with TensorFlow 2.0
Speakers Laurence Moroney (Google)
Conference O’Reilly TensorFlow World
Conf Tag
Location Santa Clara, California
Date October 28-31, 2019
URL Talk Page
Slides Talk Slides
Video

Get a programmer’s perspective on machine learning with Laurence Moroney, from the basics all the way up to building complex computer vision scenarios using convolutional neural networks and natural language processing with recurrent neural networks. The tutorial is light on math and theory and heavy on code. You’ll start by learning the concepts of training versus programming, creating a very simple example where a neural network is trained to recognize patterns. This extends into computer vision with a scenario where you train a neural network to recognize items of clothing and branch into more complex images to learn how convolutions can be used to extract features in images so you can identify a cat by its ears or a horse by its snout. You’ll then switch gears and look into some natural language processing, learning how to tokenize words, train neural networks to classify sentences in context, and maybe even do some basic text generation of your own. This will equip you with an understanding of how neural networks, machine learning, and deep learning are a new paradigm to open up new scenarios for you to build against.

recurrent neural network code tutorial math tensorflow ml network programming deep learning machine learning computer vision neural network
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