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.
Informações sobre o curso
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- 5 stars63,58%
- 4 stars23,60%
- 3 stars5,57%
- 2 stars4,09%
- 1 star3,13%
Principais avaliações do DEEP NEURAL NETWORKS WITH PYTORCH
Good introduction of PyTorch. There are some minor code errors and inconsistencies in the material but generally not difficult to figure it out.
Very intensive course. Could do more training labs. But this is definitely a very dense course. Extremely helpful to get started on ML/Deep Learning.
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!
Good pacing, great examples and the assignments are doable within the time allocated for them. Combines both technical information and applied code.
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