課程概述

The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered. Finally, several other Deep learning methods will be covered. Learning Outcomes: After completing this course, learners will be able to: • explain and apply their knowledge of Deep Neural Networks and related machine learning methods • know how to use Python libraries such as PyTorch for Deep Learning applications • build Deep Neural Networks using PyTorch...

學生對 IBM 提供的 Deep Neural Networks with PyTorch 的評價和反饋

課程概述

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26 - Deep Neural Networks with PyTorch 的 50 個評論（共 174 個）

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學生對 IBM 提供的 Deep Neural Networks with PyTorch 的評價和反饋

課程概述

熱門審閱

26 - Deep Neural Networks with PyTorch 的 50 個評論（共 174 個）

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熱門在線課程

熱門在線專項課程

在線證書

在線學位課程

Coursera

社區

更多