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 stars
- 4 stars
- 3 stars
- 2 stars
- 1 star
來自DEEP NEURAL NETWORKS WITH PYTORCH的熱門評論
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.
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!
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.
It was a LONG course, very packed with info. But, I feel like I certainly learned a lot and have a great foundation for further learning.
Good, thorough course. Does not hold the student to any kind of standard or accountability and quizzes are ridiculously easy to pass.
It is freeaaakin hard if you take the whole IBM AI ENGINEERING Professional Cert in the duration of a trial period.
The course is interesting and well organized but the quiz are not challenging and full of typos.
More graded coding assignments would have been better, but content is good!
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
關於 IBM AI Engineering 專業證書