Neural Network Tutorials - Herong's Tutorial Examples - 1.20, by Dr. Herong Yang
What Is TensorFlow
This section provides a quick introduction on TensorFlow, which is an end-to-end open source platform for machine learning with APIs for Python, C++ and many other programming languages.
What Is TensorFlow? TensorFlow is an end-to-end open source platform for machine learning with APIs for Python, C++ and many other programming languages. TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neural networks research.
TensorFlow is designed with 2 key concepts, Tensor and Flow, as described below.
1. Tensor - A tensor is a multidimensional array with elements of the same data type. A tensor is also called a multidimensional matrix, or vector.
2. Flow (Tensor Flow Graph) - A Tensor Flow Graph is a directed graph representing an expression of multiple tensor operations. In tensor flow graph, a node represents a single tensor operation and an edge represents a single tensor flowing from one operation into another operation.
Here is a tensor flow graph representing the tensor operation of [a] = ([b]+[c])*([c]+), if we use [.] to as the tensor notation.
With this Tensor Flow Graph concept, TensorFlow is able to provide you a platform for machine learning with neural networks. With TensorFlow, you can actually construct and run any array based computational models.
For more information, go to TensorFlow Website at https://www.tensorflow.org.
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