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Intro to PyTorch and Neural Networks

Offered By: Codecademy

Tags

PyTorch Courses Predictive Modeling Courses Model Evaluation Courses Activation Functions Courses Loss Functions Courses

Course Description

Overview

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Learn how to use PyTorch to build, train, and test artificial neural networks in this course.

Ready to start your journey into Neural Networks and PyTorch? In this course, you will learn how to create, train, and test artificial neural networks in PyTorch, one of the most popular deep learning frameworks in Python. You will learn about common loss functions and optimizer algorithms while building working neural networks to make predictions about real-world datasets.


* Build neural networks in PyTorch

* Define activation and loss functions

* Evaluate neural network performance

* Create real-world predictive models


Syllabus

  • Intro to PyTorch and Neural Networks: Learn how to create, train, and test artificial neural networks in PyTorch.
    • Lesson: Intro to PyTorch and Neural Networks
    • Project: Predicting Electric Vehicle Charging Loads
    • Quiz: Intro to PyTorch and Neural Networks
    • Informational: Next Steps

Taught by

Kenny Lin

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