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Learner Reviews & Feedback for Introduction to Neural Networks and PyTorch by IBM

4.4

stars

1,884 ratings

About the Course

PyTorch is one of the top 10 highest paid skills in tech (Indeed). As the use of PyTorch for neural networks rockets, professionals with PyTorch skills are in high demand. This course is ideal for AI engineers looking to gain job-ready skills in PyTorch that will catch the eye of an employer. AI developers use PyTorch to design, train, and optimize neural networks to enable computers to perform tasks such as image recognition, natural language processing, and predictive analytics. During this course, you’ll learn about 2-D Tensors and derivatives in PyTorch. You’ll look at linear regression prediction and training and calculate loss using PyTorch. You’ll explore batch processing techniques for efficient model training, model parameters, calculating cost, and performing gradient descent in PyTorch. Plus, you’ll look at linear classifiers and logistic regression. Throughout, you’ll apply your new skills in hands-on labs, and at the end, you’ll complete a project you can talk about in interviews. If you’re an aspiring AI engineer with basic knowledge of Python and mathematical concepts, who wants to get hands-on with PyTorch, enroll today and get set to power your AI career forward!...

Top reviews

Jul 20, 2020

The right level of detail so that you can dive in. I wish there had been a week to cover RNNs as well though, in particular the best way to handle variable length sequences for RNNs :)

Jul 12, 2020

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!

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By Kartik S

•

Oct 26, 2020

the explanation is not in detail. Course Structure is confusing as well. Sometimes the concepts taught are not entirely correct. Overall not a good experience.