Learner Reviews & Feedback for Deep Learning with PyTorch by IBM

4.5

stars

30 ratings

About the Course

This course advances from fundamental machine learning concepts to more complex models and techniques in deep learning using PyTorch. This comprehensive course covers techniques such as Softmax regression, shallow and deep neural networks, and specialized architectures, such as convolutional neural networks. In this course, you will explore Softmax regression and understand its application in multi-class classification problems. You will learn to train a neural network model and explore Overfitting and Underfitting, multi-class neural networks, backpropagation, and vanishing gradient. You will implement Sigmoid, Tanh, and Relu activation functions in Pytorch. In addition, you will explore deep neural networks in Pytorch using nn Module list and convolution neural networks with multiple input and output channels. You will engage in hands-on exercises to understand and implement these advanced techniques effectively. In addition, at the end of the course, you will gain valuable experience in a final project on a convolutional neural network (CNN) using PyTorch. This course is suitable for all aspiring AI engineers who want to gain advanced knowledge on deep learning using PyTorch. It requires some basic knowledge of Python programming and basic mathematical concepts such as gradients and matrices....

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1 - 11 of 11 Reviews for Deep Learning with PyTorch

By JAWAD A

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Feb 9, 2025

Perfect course with the right amount of difficulty and perfect learning

By Arash Y

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Feb 24, 2025

It was Fun Thanks for That ! Python is pure Love!

By Alima A

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Feb 11, 2025

Its amazing course

By Manvi G

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Feb 11, 2025

Amazing content!!

By Haroon

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Feb 11, 2025

Excellent course.

By lavanya s

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Feb 11, 2025

Excellent Course

By Sweta S

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Feb 11, 2025

Excellent Course

By Sa S

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Feb 12, 2025

Awesome!

By David C

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Feb 28, 2025

Interesting course to learn the coding aspects of neural; however, the theoretical and mathematical component could be improved and/or corrected, for example, showing the gradient of ReLU at zero as a vertical line.

By Bogdan B

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Mar 2, 2025

Poorly structured and explained. Took this course after Deep Learning with Keras and the Keras API is much easier to understand. This course is very bland and just throws a bunch of code at you. Found it difficult to get through and did noy understand much from it.