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 stars64,29 %
- 4 stars23 %
- 3 stars5,73 %
- 2 stars3,95 %
- 1 star3,02 %
Top-Bewertungen von DEEP NEURAL NETWORKS WITH PYTORCH
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.
Amazing course for a beginner in Deep Learning & Pytorch.
I gave 4 stars as I expected it to be more pytorch heavy.
Overall, a really good crafted course.
Good pacing, great examples and the assignments are doable within the time allocated for them. Combines both technical information and applied code.
It was a very informative and interesting lecture. I learn a lot about the details when using PyTorch to build and train a deep neural network. I am so thankful.
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