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Course Outline
Introduction
- Overview of Horovod features and concepts for government use
- Understanding the supported frameworks for government applications
Installing and Configuring Horovod for Government
- Preparing the hosting environment for government systems
- Building Horovod for TensorFlow, Keras, PyTorch, and Apache MXNet in a government context
- Running Horovod in government environments
Running Distributed Training for Government
- Modifying and running training examples with TensorFlow for government projects
- Modifying and running training examples with Keras for government initiatives
- Modifying and running training examples with PyTorch for government operations
- Modifying and running training examples with Apache MXNet for government applications
Optimizing Distributed Training Processes for Government
- Running concurrent operations on multiple GPUs in a government setting
- Tuning hyperparameters for enhanced performance in government use cases
- Enabling performance autotuning for government systems
Troubleshooting for Government
Summary and Conclusion for Government
Requirements
- An understanding of machine learning, with a focus on deep learning techniques.
- Familiarity with machine learning libraries such as TensorFlow, Keras, PyTorch, and Apache MXNet.
- Proficiency in Python programming.
Audience for government
- Developers
- Data scientists
7 Hours
