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Deep Neural Networks with PyTorch(으)로 돌아가기

IBM의 Deep Neural Networks with PyTorch 학습자 리뷰 및 피드백

4.4
별점
1,020개의 평가
226개의 리뷰

강좌 소개

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. Learning Outcomes: After completing this course, learners will be able to: • explain and apply their knowledge of Deep Neural Networks and related machine learning methods • know how to use Python libraries such as PyTorch for Deep Learning applications • build Deep Neural Networks using PyTorch...

최상위 리뷰

SY
2020년 4월 29일

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!!

RA
2020년 5월 15일

This is not a bad course at all. One feedback, however, is making the quizzes longer, and adding difficult questions especially concept-based one in the quiz will be more rewarding and valuable.

필터링 기준:

Deep Neural Networks with PyTorch의 227개 리뷰 중 226~227

교육 기관: Walter c

2021년 6월 20일

The agenda is good but it is not well explained.

교육 기관: Javier J M

2021년 2월 22일

Sucks!!