PyTorch: The Complete Guide 2022

Learn how to create state of the art neural networks for deep learning with Facebook's PyTorch Deep Learning library!

4.67 (3 reviews)
Udemy
platform
English
language
Data Science
category
instructor
PyTorch: The Complete Guide 2022
102
students
9.5 hours
content
Jan 2022
last update
$54.99
regular price

What you will learn

Pandas

Pytorch

Numpy

Artificial Neural Networks (ANN)

Generative adversarial network (GAN)

Convolution Neural Network (CNN)

Recurrent Neural Network (RNN)

Google Colab .

Matplotlib.

Long Short Term Memory (LSTM)

Language Model

Reinforcement Learning

OpenAI Gym

Why take this course?

Welcome to the best online course for learning about Pytorch!


Although Google's Deep Learning library Tensorflow has gained massive popularity over the past few years, PyTorch has been the library of choice for professionals and researchers around the globe for deep learning and artificial intelligence.

Is it possible that Tensorflow is popular only because Google is popular and used effective marketing?

Why did Tensorflow change so significantly between version 1 and version 2? Was there something deeply flawed with it, and are there still potential problems?

It is less well-known that PyTorch is backed by another Internet giant, Facebook (specifically, the Facebook AI Research Lab - FAIR). So if you want a popular deep learning library backed by billion dollar companies and lots of community support, you can't go wrong with PyTorch. And maybe it's a bonus that the library won't completely ruin all your old code when it advances to the next version. ;)

On the flip side, it is very well-known that all the top AI shops (ex. OpenAI, Apple, and JPMorgan Chase) use PyTorch. OpenAI just recently switched to PyTorch in 2022, a strong sign that PyTorch is picking up steam.


In this course you will learn everything you need to know to get started with Pytorch, including:

  • NumPy

  • Pandas

  • Tensors with PyTorch

  • Neural Network Theory

    • Perceptrons

    • Networks

    • Activation Functions

    • Cost/Loss Functions

    • Backpropagation

    • Gradients

  • Artificial Neural Networks

  • Convolutional Neural Networks

  • Recurrent Neural Networks

  • and much more!

By the end of this course you will be able to create a wide variety of deep learning models to solve your own problems with your own data sets.

So what are you waiting for? Enroll today and experience the true capabilities of PyTorch! I'll see you inside the course!

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4463936
udemy ID
12/28/2021
course created date
2/25/2022
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