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Let's get started

Welcome to LearningTensorFlow.com! Our aim is to teach TensorFlow from the ground up, without requiring you to know or learn, deep learning at the same time. We found many tutorials were too heavy on the machine learning parts, and skipped over important details of how it is implemented in TensorFlow, making it difficult to start creating your own programs.

Choose your own adventure, by selecting which set of TensorFlow tutorials you'd like to start with. If you are new to TensorFlow, we recommend you start with Basics. If you have some experience, check out Learning or Distributing.

Install

Don't have TensorFlow on your computer yet? Use the official TensorFlow instructions here to get started.


Be sure to select whether you want to use your GPU or not - you'll need it in a later tutorial, but if you don't have a supported GPU, that's OK.

Learn about arrays, matrices and tensors in our lessons focused on introducing the basic concepts of the underlying mathematics behind TensorFlow and its use.

These tutorials build up the skills needed to implement algorithms in TensorFlow from research and technical documents.

Starting from scratch? Our tutorials assume no data mining knowledge and no previous TensorFlow experience.

We do ask that you have some Python experience. Check out our Resources page if you don't.

What about data mining? If you know the basics of TensorFlow, and want to get started on the Machine Learning, start here.

Our tutorials are heavy on application, light on theory. Checkout our Examples page for more complex examples

Distributed computing is where TensorFlow starts to shine. These tutorials will look at how to use your computer(s) to the limits to do graph computation.

The tutorials assume the previous lessons, so only go here if you are confident with the basics.

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This book is the ultimate guide to getting started with using data in your business, with a non-technical view and focusing on achieving good outcomes. We don't get bogged down by technical detail or complex algorithms.

For additional offers, including a premium package, see this page.

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You can also support LearningTensorFlow.com by becoming a patron at Patreon. If we have saved you trawling through heavy documentation, or given you a pointer on where to go next, help us to create new lessons and keep the site running.

You'll also get access to extra content and updates not available on LearningTensorFlow.com!

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Note: despite the title, this book has no relationship to LearningTensorFlow.com

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