![Deep Learning Projects with PyTorch [Video] Book Cover](https://proxy-ga.blitzz.co/proxy/123456/web.archive.org/web/20180728003900/https:/www.packtpub.com/sites/default/files/bookretailers/V09915.png "Deep Learning Projects with PyTorch [Video] from Packt")
![Deep Learning Projects with PyTorch [Video] Book Cover](https://web.archive.org/web/20180728003900im_/https://d1ldz4te4covpm.cloudfront.net/sites/default/files/imagecache/featured_book_block/bookretailers/V09915.png "Deep Learning Projects with PyTorch [Video] from Packt")
![Deep Learning Projects with PyTorch [Video] Book Cover](https://proxy-ga.blitzz.co/proxy/123456/web.archive.org/web/20180728003900im_/https:/www.packtpub.com/sites/default/files/blank.gif "Deep Learning Projects with PyTorch [Video] from Packt")
![Deep Learning with PyTorch [Video] Book Cover](https://web.archive.org/web/20180728003900im_/https://dz13w8afd47il.cloudfront.net/sites/default/files/imagecache/featured_book_block/bookretailers/V08781_low.png "Deep Learning with PyTorch [Video] from Packt")
Video Description
PyTorch is a Deep Learning framework that is a boon for researchers and data scientists. It supports Graphic Processing Units and is a platform that provides maximum flexibility and speed. With PyTorch, you can dynamically build neural networks and easily perform advanced Artificial Intelligence tasks.
The course starts with the fundamentals of PyTorch and how to use basic commands. Next, you’ll learn about Convolutional Neural Networks (CNN) through an example of image recognition, where you’ll look into images from a machine perspective.
The next project shows you how to predict character sequence using Recurrent Neural Networks (RNN) and Long Short Term Memory Network (LSTM). Then you’ll learn to work with autoencoders to detect credit card fraud. After that, it’s time to develop a system using Boltzmann Machines, where you’ll recommend whether to watch a movie or not.
We’ll continue with Boltzmann Machines, where you’ll learn to give movie ratings using AutoEncoders. In the end, you’ll get to develop and train a model to recognize a picture or an object from a given image using Deep Learning, where we’ll not only detect the shape, but also the color of the object.
By the end of the course, you’ll be able to start using PyTorch to build Deep Learning models by implementing practical projects in the real world. So, grab this course as it will take you through interesting real-world projects to train your first neural nets.
Style and Approach
This course takes a practical approach and is filled with real-world examples to help you create your own application using PyTorch.
![Deep Learning and Neural Networks in PyTorch for Beginners [Video] Book Cover](https://web.archive.org/web/20180728003900im_/https://d255esdrn735hr.cloudfront.net/sites/default/files/imagecache/featured_book_block/bookretailers/V11717_low.png "Deep Learning and Neural Networks in PyTorch for Beginners [Video] from Packt")
![Hands-on NLP with NLTK and Scikit-learn [Video] Book Cover](https://web.archive.org/web/20180728003900im_/https://dz13w8afd47il.cloudfront.net/sites/default/files/imagecache/featured_book_block/bookretailers/V11009_low_0.png "Hands-on NLP with NLTK and Scikit-learn [Video] from Packt")
![AWS SageMaker, Machine Learning and AI with Python [Video] Book Cover](https://web.archive.org/web/20180728003900im_/https://d255esdrn735hr.cloudfront.net/sites/default/files/imagecache/featured_book_block/bookretailers/V11568_Low.png "AWS SageMaker, Machine Learning and AI with Python [Video] from Packt")