| Description
| This course introduces the basic concepts of DL, mathematical model algorithms, and engineering implementation principles, and understands the key implementation techniques of DL with the TensorFlow Open Source Framework (OSF). The course experiment builds the TensorFlow development environment with streamlined codes and model description files to design a complete DNN. This course introduces the principles and practical aspects of: 1.) ML, DL and DNN, 2.) The features of TensorFlow and OSF installation, 3.) Implementation of Convolution Neural Network (CNN), Recurrent Neural Network (RNN) and Restricted Boltzmann Machine (RBM), 4.) Introduction of Reinforcement Learning, 5.) DL application practices.
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