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.
이 강좌에 대하여
- 5 stars64.41%
- 4 stars23.11%
- 3 stars5.55%
- 2 stars3.89%
- 1 star3.01%
DEEP NEURAL NETWORKS WITH PYTORCH의 최상위 리뷰
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.
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.
Good pacing, great examples and the assignments are doable within the time allocated for them. Combines both technical information and applied code.
The material is good. I found the assignments a bit too easy. A bit more challenge would be welcome. I found the artificial voice with the lectures to be distracting. The AI isn't quite good enough.