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Implementing Multi-layer Neural Networks with TFLearn

Deep learning is one of the hottest topics for machine learning engineers. In this course, you'll quickly jump into building your first neural network using TFLearn on top of Tensorflow.

Thomas Henson - Pluralsight course - Implementing Multi-layer Neural Networks with TFLearn
by Thomas Henson

What you'll learn

TFLearn offers machine learning engineers the ability to build Tensorflow neural networks with minimal use of coding. In this course, Implementing Multi-layer Neural Networks with TFLearn, you’ll learn foundational knowledge and gain the ability to build Tensorflow neural networks. First, you’ll explore how deep learning is used to accelerate artificial intelligence. Next, you’ll discover how to build convolutional neural networks. Finally, you’ll learn how to deploy both deep and generative neural networks. When you’re finished with this course, you’ll have the skills and knowledge of deep learning needed to build the next generation of artificial intelligence.

Table of contents

About the author

Thomas Henson - Pluralsight course - Implementing Multi-layer Neural Networks with TFLearn
Thomas Henson

Thomas is a Senior Software Engineer and Certified ScrumMaster. He spends most of his time working with the Hortonwork Data Platform and Agile Coaching.

More Courses by Thomas