Zero to ML hero with TensorFlow 2.0
Who is this presentation for?
- Software developers and business and technical decision makers
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.
- A basic understanding of programming, particularly in Python
Materials or downloads needed in advance
- A laptop with a browser installed
What you'll learn
- Understand how ML works—in particular, how programming it works with TensorFlow
Laurence Moroney is a developer advocate on the Google Brain team at Google, working on TensorFlow and machine learning. He’s the author of dozens of programming books, including several best sellers, and a regular speaker on the Google circuit. When not Googling, he’s also a published novelist, comic book writer, and screenwriter.
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