This course covers the final workflow of a deep studying undertaking, applied utilizing PyTorch in Google Colab. At the tip of the course, college students will probably be proficient at utilizing Google Colab in addition to PyTorch in their very own tasks. Students may also study in regards to the theoretical foundations for numerous deep studying fashions and methods, in addition to tips on how to implement them utilizing PyTorch. Finally, the course ends by providing an summary on common deep studying and the way to consider issues within the discipline; college students will acquire a high-level understanding of the position deep studying performs within the discipline of AI.
Learn tips on how to make the most of Google Colab as an internet computing platform in deep studying tasks, together with operating Python code, utilizing a free GPU, and dealing with exterior recordsdata and folders
Understand the final workflow of a deep studying undertaking
Examine the varied APIs (datasets, modeling, coaching) PyTorch provides to facilitate deep studying
Learn in regards to the theoretical foundation for numerous deep studying fashions akin to convolutional networks or residual networks and what issues they handle
Gain an summary understanding of deep studying within the context of the factitious intelligence discipline and its greatest practices