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.
Über diesen Kurs
- 5 stars64,18 %
- 4 stars23,03 %
- 3 stars5,73 %
- 2 stars4,01 %
- 1 star3,03 %
Top-Bewertungen von DEEP NEURAL NETWORKS WITH PYTORCH
The course content was very well presented and was relatively easy to understand even when the pytorch framework is a bit complex. Thank you!
By this course I can understand the basic concept for building neural network or deep lerning model using PyTorch. Very Good course to beginner.
Wonderful course!!! Best among all the courses under AI Engineer Certificate by IBM. Deep learning always haunted me with the maths involved but now I get a very good start with this.
Great introduction to deep learning with pytorch. It would help if the notebooks in the labs take shorter to run so that the students can experiment with the code and the models.
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