PyTorch for Deep Learning and Computer Vision
4.6 (982 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
5,771 students enrolled

PyTorch for Deep Learning and Computer Vision

Build Highly Sophisticated Deep Learning and Computer Vision Applications with PyTorch
4.6 (982 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
5,771 students enrolled
Last updated 2/2020
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Current price: $129.99 Original price: $199.99 Discount: 35% off
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This course includes
  • 12.5 hours on-demand video
  • 22 articles
  • 3 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Implement Machine and Deep Learning applications with PyTorch
  • Build Neural Networks from scratch
  • Build complex models through the applied theme of Advanced Imagery and Computer Vision
  • Solve complex problems in Computer Vision by harnessing highly sophisticated pre-trained models
  • Use style transfer to build sophisticated AI applications
Course content
Expand all 136 lectures 16:27:44
+ Intro to Tensors - PyTorch
8 lectures 31:03
Intro
00:18
Vector Operations
05:23
2 Dimensional Tensors
05:30
Slicing 3D Tensors
03:02
Matrix Multiplication
03:21
Gradient with PyTorch
04:23
Outro
00:13
+ Linear Regression - PyTorch
12 lectures 53:57
Intro
00:44
Making Predictions
06:15
Linear Class
04:29
Custom Modules
08:08
Creating Dataset
10:35
Loss Function
03:33
Gradient Descent
04:41
Mean Squared Error
03:15
Training - Code Implementation
11:36
Getting Weird Results?
00:09
Outro
00:31
Summary
00:01
+ Perceptrons - PyTorch
8 lectures 51:09
Intro
00:34
What is Deep Learning
01:19
Creating Dataset
09:34
Perceptron Model
11:56
Model Setup
11:22
Model Training
10:38
Model Testing
05:23
Outro
00:23
+ Deep Neural Networks - PyTorch
9 lectures 54:16
Intro
00:28
Non-Linear Boundaries
03:11
Architecture
09:06
Feedforward Process
07:46
Error Function
04:10
Backpropagation
05:03
Code Implementation
08:49
Testing Model
15:21
Outro
00:22
+ Image Recognition - PyTorch
11 lectures 01:34:09
Intro
00:36
MNIST Dataset
05:50
Training and Test Datasets
12:39
Image Transforms
16:26
Important Update - Bug fix
00:17
Neural Network Implementation
30:44
Neural Network Validation
12:21
Test Links
00:01
Final Tests
13:26
A note on adjusting batch size
01:28
Outro
00:21
+ Convolutional Neural Networks - PyTorch
7 lectures 01:23:05
Convolutions and MNIST
06:09
Convolutional Layer
18:11
Convolutions II
08:07
Pooling
14:11
Fully Connected Network
06:23
Neural Network Implementation with PyTorch
12:46
Model Training with PyTorch
17:18
+ CIFAR 10 Classification - PyTorch
4 lectures 31:52
The CIFAR 10 Dataset
01:44
Testing LeNet
09:51
Hyperparameter Tuning
07:52
Data Augmentation
12:25
+ Transfer Learning - PyTorch
3 lectures 42:17
Pre-trained Sophisticated Models
14:40
Github Link for Dataset
00:03
AlexNet and VGG16
27:34
Requirements
  • No experience is required
Description

PyTorch has rapidly become one of the most transformative frameworks in the field of Deep Learning. Since its release, PyTorch has completely changed the landscape in the field of deep learning due to its flexibility, and how easy it is to use when building Deep Learning models.

Deep Learning jobs command some of the highest salaries in the development world. This course is meant to take you from the complete basics, to building state-of-the art Deep Learning and Computer Vision applications with PyTorch.

Learn & Master Deep Learning with PyTorch in this fun and exciting course with top instructor Rayan Slim. With over 44000 students, Rayan is a highly rated and experienced instructor who has followed a "learn by doing" style to create this amazing course.

You'll go from beginner to Deep Learning expert and your instructor will complete each task with you step by step on screen.

By the end of the course, you will have built state-of-the art Deep Learning and Computer Vision applications with PyTorch. The projects built in this course will impress even the most senior developers and ensure you have hands on skills that you can bring to any project or company.

This course will show you to:

  • Learn how to work with the tensor data structure

  • Implement Machine and Deep Learning applications with PyTorch

  • Build neural networks from scratch

  • Build complex models through the applied theme of advanced imagery and Computer Vision

  • Learn to solve complex problems in Computer Vision by harnessing highly sophisticated pre-trained models

  • Use style transfer to build sophisticated AI applications that are able to seamlessly recompose images in the style of other images.

No experience required. This course is designed to take students with no programming/mathematics experience to accomplished Deep Learning developers.

This course also comes with all the source code and friendly support in the Q&A area.

Who this course is for:

  • Anyone with an interest in Deep Learning and Computer Vision

  • Anyone (no matter the skill level) who wants to transition into the field of Artificial Intelligence

  • Entrepreneurs with an interest in working on some of the most cutting edge technologies

  • All skill levels are welcome!

Who this course is for:
  • Anyone with an interest in Deep Learning and Computer Vision
  • Anyone (no matter the skill level) who wants to transition into the field of Artificial Intelligence
  • Entrepreneurs with an interest in working on some of the most cutting edge technologies
  • All skill levels are welcome!