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This tutorial will teach how to gain access to the system, how to interact with the system through Open OnDemand interface, including Jupiter notebook, and through command line interface.
This tutorial will cover basic machine learning techniques, such as Linear Regression, Decision Tree, Support Vector Machine, Naive Bayes, K- Nearest Neighbors, K-Means, and Random Forest, using TensorFlow on HAL system.
This tutorial will introduce how machine learning can be accomplished with neural networks and will go over various examples from simple dense networks to convolutional network architectures using TensorFlow on HAL system.
This tutorial will introduce sequence models, such as RNN and LSTM, and how these models can be implemented with TensorFlow on HAL system.