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.
About this Course
- 5 stars64.40%
- 4 stars23.12%
- 3 stars5.60%
- 2 stars3.92%
- 1 star2.96%
TOP REVIEWS FROM 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.
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.
Good introduction of PyTorch. There are some minor code errors and inconsistencies in the material but generally not difficult to figure it out.
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