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.
- 5 stars64.26%
- 4 stars23.02%
- 3 stars5.73%
- 2 stars3.95%
- 1 star3.02%
來自DEEP NEURAL NETWORKS WITH PYTORCH的熱門評論
In-depth course, goes in much more detail than the usual introductory courses, also emphasizes on practical hands on rather than theoretical knowledge
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.
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!
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.