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.
À propos de ce cours
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- 5 stars63,54 %
- 4 stars23,60 %
- 3 stars5,59 %
- 2 stars4,10 %
- 1 star3,14 %
Meilleurs avis pour DEEP NEURAL NETWORKS WITH PYTORCH
Good pacing, great examples and the assignments are doable within the time allocated for them. Combines both technical information and applied code.
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. I love the way the course was presented. There were a lot of practical and visual examples explaining each module. It is highly recommended!
The course content was very well presented and was relatively easy to understand even when the pytorch framework is a bit complex. Thank you!
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