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
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!
Awesome! This course gives me the basic workflow for using machine learning technique in my research! The materials in the form of Jupyter lab really help!
An extremely good course for anyone starting to build deep learning models. I am very satisfied at the end of this course as i was able to code models easily using pytorch. Definitely recomended!!
SO far, this has been the best designed and most informative of the four courses that I have taken so far in the IBM AI Engineering Certification.