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DevelopmentData SciencePyTorch

PyTorch for Deep Learning and Computer Vision

Build Highly Sophisticated Deep Learning and Computer Vision Applications with PyTorch
Rating: 4.7 out of 54.7 (1,735 ratings)
10,607 students
Created by Rayan Slim, Jad Slim, Amer Sharaf, Sarmad Tanveer
Last updated 9/2020
English
English [Auto]

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

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!

Featured review

Tom Lasinski
Tom L.
13 courses
5 reviews
Rating: 4.5 out of 52 years ago
Very impressed by thorough explanation of each of the coding steps, in particular, transition between numpy and torch. Also, the circle is a good introduction to cnn; other authors jump directly into complicated problems like mnist. The MNIST lessons clearly explained how to observe over or under fitting by comparing the train set and test set accuracies and losses

Instructors

Rayan Slim
Developer
Rayan Slim
  • 4.6 Instructor Rating
  • 17,700 Reviews
  • 142,815 Students
  • 7 Courses

Rayan is a full-stack software developer based in Ottawa, Canada.

Rayan has been appointed as an acting tech lead at Canada's IRCC. His main role is to set up infrastructure monitoring tools to extract health metrics from cloud-native applications.

Rayan also takes leadership roles as he guides other developers towards building Spring Boot applications that implement Enterprise Integration Patterns using the Apache Camel framework. His supervision extends to showing developers how to deploy their applications on the Red Hat Openshift platform using the Kubernetes package manager Helm.

Outside of his daily work, Rayan loves to explore new technologies. He is deeply passionate about Artificial Intelligence and Data Visualization.

In Rayan's free time, he loves to teach!

Jad Slim
Developer
Jad Slim
  • 4.6 Instructor Rating
  • 18,077 Reviews
  • 134,086 Students
  • 8 Courses

Jad studied mechanical engineering at the University of Ottawa. Jad also has extensive experience in software development, cloud development, machine learning, computer vision, mathematical modeling, computer simulation, and intelligent systems. Jad has also developed many deep learning applications, and is currently pursuing an interest in autonomous machines and Full Stack Development.

Amer Sharaf
Developer
Amer Sharaf
  • 4.7 Instructor Rating
  • 5,337 Reviews
  • 57,678 Students
  • 2 Courses

   Hi I'm Amer. I'm a full-time developer with a specialized interest in Artificial intelligence (AI).  AI is now taking on more sophisticated roles that can truly amplify human capabilities.

   With a background in Mechanical Engineering and computer science I have always looked for ways to use the power of AI to create practical solutions that revolutionize the way we live.

I aim to make artificial intelligence more accessible to all students, no matter the skill level! 

Sarmad Tanveer
Data Scientist
Sarmad Tanveer
  • 4.6 Instructor Rating
  • 9,791 Reviews
  • 52,499 Students
  • 3 Courses

Hi! I'm Sarmad, and I have graduate level expertise in Mechanical Engineering. My main areas of interest and research include autonomous robotics, self driving car technology and machine learning.

In my spare time, I enjoy teaching courses on Udemy and sharing my knowledge with all of you!



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