Understanding the Foundations of TensorFlow

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Understanding the Foundations of TensorFlow
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 3 Hours | 328 MB
Genre: eLearning | Language: English


This course introduces TensorFlow, an open source data flow library for numerical computations using data flow graphs.
In this course, Understanding the Foundations of TensorFlow, you'll learn the TensorFlow library from very first principles. First, you'll start with the basics of machine learning using linear regression as an example and focuses on understanding fundamental concepts in TensorFlow. Next, you'll discover how to apply them to machine learning, the concept of a Tensor, the anatomy of a simple program, basic constructs such as constants, variables, placeholders, sessions, and the computation graph. Then, you'll be introduced to TensorBoard, the visualization tool used to view and debug the data flow graphs. You'll work with basic math operations and image transformations to see how common computations are performed. Finally, you'll solve a real world machine learning problem using the MNIST handwritten dataset and the k-nearest-neighbours algorithm. By the end of this course, you'll have a better understanding of the foundations of TensorFlow.


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