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.
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IBM Skills NetworkAbout this Course
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Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Intermediate Level
Approx. 30 hours to complete
English
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessFlexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Intermediate Level
Approx. 30 hours to complete
English
Could your company benefit from training employees on in-demand skills?
Try Coursera for Business
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Syllabus - What you will learn from this course
5 hours to complete
Tensor and Datasets
5 hours to complete
6 videos (Total 44 min)
2 hours to complete
Linear Regression
2 hours to complete
7 videos (Total 35 min)
3 hours to complete
Linear Regression PyTorch Way
3 hours to complete
5 videos (Total 21 min)
2 hours to complete
Multiple Input Output Linear Regression
2 hours to complete
4 videos (Total 18 min)
2 hours to complete
Logistic Regression for Classification
2 hours to complete
4 videos (Total 31 min)
2 hours to complete
Softmax Rergresstion
2 hours to complete
3 videos (Total 18 min)
3 hours to complete
Shallow Neural Networks
3 hours to complete
6 videos (Total 33 min)
Reviews
- 5 stars64.30%
- 4 stars23.03%
- 3 stars5.72%
- 2 stars3.89%
- 1 star3.05%
TOP REVIEWS FROM DEEP NEURAL NETWORKS WITH PYTORCH
by RDSep 29, 2021
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.
by TGJan 10, 2020
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.
by YWOct 4, 2022
Not only did I gain the basic knowledge of deep learning, but also learned Pytorch. It is a good course, however, there is still a lot more to go in the area of Deep learning,
by SWAug 4, 2022
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.
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