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Introduction to Deep Learning with PyTorch

Learn to create deep learning models with the PyTorch library.

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4 Hours17 Videos53 Exercises15,926 Learners
4300 XP

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Course Description

Neural networks have been at the forefront of Artificial Intelligence research during the last few years, and have provided solutions to many difficult problems like image classification, language translation or Alpha Go. PyTorch is one of the leading deep learning frameworks, being at the same time both powerful and easy to use. In this course you will use PyTorch to first learn about the basic concepts of neural networks, before building your first neural network to predict digits from MNIST dataset. You will then learn about convolutional neural networks, and use them to build much more powerful models which give more accurate results. You will evaluate the results and use different techniques to improve them. Following the course, you will be able to delve deeper into neural networks and start your career in this fascinating field.

  1. 1

    Introduction to PyTorch

    Free

    In this first chapter, we introduce basic concepts of neural networks and deep learning using PyTorch library.

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    Introduction to PyTorch
    50 xp
    Creating tensors in PyTorch
    100 xp
    Matrix multiplication
    100 xp
    Forward propagation
    50 xp
    Forward pass
    100 xp
    Backpropagation by auto-differentiation
    50 xp
    Backpropagation by hand
    50 xp
    Backpropagation using PyTorch
    100 xp
    Calculating gradients in PyTorch
    100 xp
    Introduction to Neural Networks
    50 xp
    Your first neural network
    100 xp
    Your first PyTorch neural network
    100 xp

In the following tracks

Deep Learning

Collaborators

Hadrien LacroixHillary Green-Lerman
Ismail Elezi Headshot

Ismail Elezi

Researcher PHD Student at Ca' Foscari University of Venice

I am a third year PhD Student of Deep Learning, supervised by professor Marcello Pelillo at Ca' Foscari, University of Venice. During my PhD, I did an exchange period at ZHAW Datalab (Switzerland) working with professor Thilo Stadelmann. From January on, I am visiting professor's Laura Leal-Taixe lab in Technical University of Munich.
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