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Introduction to Neural Networks and PyTorch

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...

By Joseph Santarcangelo on Coursera

About This 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!

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Frequently Asked Questions

How much does Introduction to Neural Networks and PyTorch cost?

Visit the Introduction to Neural Networks and PyTorch course page for current pricing and available discounts.

Who teaches Introduction to Neural Networks and PyTorch?

Introduction to Neural Networks and PyTorch is taught by Joseph Santarcangelo, IBM.

What skill level is Introduction to Neural Networks and PyTorch for?

This course is designed for beginner learners.

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Students0
Duration3 hours
LevelBeginner
Languageen
PlatformCoursera