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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- 5 stars63.56%
- 4 stars23.72%
- 3 stars5.72%
- 2 stars3.84%
- 1 star3.13%
DEEP NEURAL NETWORKS WITH PYTORCH의 최상위 리뷰
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.
Good pacing, great examples and the assignments are doable within the time allocated for them. Combines both technical information and applied code.
Good introduction of PyTorch. There are some minor code errors and inconsistencies in the material but generally not difficult to figure it out.
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!!