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.
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- 4 stars23.09%
- 3 stars5.55%
- 2 stars3.88%
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来自DEEP NEURAL NETWORKS WITH PYTORCH的热门评论
An extremely good course for anyone starting to build deep learning models. I am very satisfied at the end of this course as i was able to code models easily using pytorch. Definitely recomended!!
Excellent Course. I love the way the course was presented. There were a lot of practical and visual examples explaining each module. It is highly recommended!
this course provides a very good and cohesive introduction to Neural Networks. I learned a lot during my journey and I recommend it for anyone interesting in the field.
Excellent course, works its way through basics to fully fledged machine learning models at a good pace. A few of the examples used in the lab code throw errors, these should be rectified