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Pluralsight

Implementing Multi-layer Neural Networks with TFLearn

via Pluralsight

Overview

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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.

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.

Syllabus

  • Course Overview 1min
  • Why Deep Learning? 18mins
  • What Is TFLearn? 24mins
  • Implementing Layers in TFLearn 38mins
  • Building Activations in TFLearn 11mins
  • Managing Data with TFLearn 18mins
  • Running Models with TFLearn 16mins

Taught by

Thomas Henson

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