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Implementing Multi-layer Neural Networks with TFLearn

by Thomas Henson

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.

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.

About the author

Thomas is a Senior Software Engineer and Certified ScrumMaster. During his career he has been involved in many projects from building web applications to setting up Hadoop clusters. Thomas's specialization is with Hortonworks Data Platform and Agile Software Development. Thomas is a proud alumnus of the University of North Alabama where he received his BBA - Computer Information System and his MBA - Information Systems. He currently resides in north Alabama with his wife and daughter, where ... more

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