TensorFlow: Getting Started

Pluralsight
Course Summary
This course shows you how to install and use TensorFlow, a leading machine learning library from Google. You'll see how TensorFlow can create a range of machine learning models, from simple linear regression to complex deep neural networks.
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Course Description
Developing sophisticated machine learning solutions is a difficult task. There are many processing steps that must be performed, and how this processing is performed is a function of not only the code you write, but also the data you use. In this course, TensorFlow: Getting Started, you'll see how TensorFlow easily addresses these concerns by learning TensorFlow from the bottom up. First, you'll be introduced to the installation process, building simple and advanced models, and utilizing additional libraries that make development even easier. Along the way, you'll learn how the unique architecture in TensorFlow lets you perform your computing on systems as small as a Raspberry Pi, and as large as a data farm. Finally, you'll explore using TensorFlow with neural networks in general, and specifically with powerful deep neural networks. By the end of this course, you'll have a solid foundation on using TensorFlow, and have the knowledge to apply TensorFlow to create your own machine learning solutions.
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Course Syllabus
Course Overview- 1m 37s
—Course Overview 1m 37sIntroduction- 15m 36s
—Introduction 3m 0s
—TensorFlow as Interface and Implementation 3m 49s
—Why Is It Called TensorFlow? 2m 39s
—Skills and Course Structure 6m 7sIntroducing TensorFlow- 31m 17sCreating Neural Networks in TensorFlow- 32m 30sDebugging and Monitoring- 23m 47sTransfer Learning with TensorFlow- 22m 15sExtending TensorFlow with Add-ons- 26m 33sSummary- 4m 15s