PyTorch for Deep Learning and Computer Vision

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Learn to build highly sophisticated deep learning and Computer Vision applications with PyTorch.

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122 on-demand videos & exercises
Level: Intermediate
English
12hrs 32mins
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What to know about this course

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 of the deep learning domain with its flexibility and has made building deep learning models easier. The development world offers some of the highest paying jobs in deep learning. In this exciting course, instructor Rayan Slim will help you learn and master deep learning with PyTorch. Having taught over 44,000 students, Rayan is a highly rated and experienced instructor who has followed a learning-by-doing style to create this course. You'll go from a beginner to deep learning expert with your instructor completing each step of the task with you. By the end of this 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 organization. All the code and supporting files for this course are available at https://github.com/PacktPublishing/PyTorch-for-Deep-Learning-and-Computer-Vision

Who's this course for?

This course is for you if you’re interested in deep learning and Computer Vision. Anyone (no matter the skill level) who wants to transition into the field of artificial intelligence and entrepreneurs with an interest in working on some of the most cutting-edge technologies will find this course useful.

What you'll learn

  • 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.
  • Solve complex problems in Computer Vision by harnessing highly sophisticated pre-trained models.
  • Use style transfer to build sophisticated AI applications.

Key Features

  • This course is designed to help you become an accomplished deep learning developer even with no experience in programming or mathematics.

Course Curriculum

About the Author

Sarmad Tanveer, Rayan Slim, Jad Slim, Amer Abdulkader

Sarmad has a deep passion for data science. He is a Mechanical Engineering graduate turned Data Scientist and had gained experience in the field while working on his very own startups. His main work focuses on creating predictive models using a combination of complex deep learning algorithms and sentiment analysis. He also has prior experience with deep learning fueled autonomous machines. In his spare time, he enjoys teaching courses and sharing his knowledge with all of you!.

Rayan Slim is a full-stack Software Developer based in Ottawa, Canada. He guides developers towards building Spring Boot applications that implement Enterprise Integration Patterns using the Apache Camel framework. His teaches developers how to deploy their applications on the Red Hat Openshift platform using the Kubernetes package manager Helm. He is experienced in setting up infrastructure monitoring tools to extract health metrics from cloud-native applications. Rayan loves to explore new technologies and is deeply passionate about Artificial Intelligence and Data Visualization.

Jad Slim studied mechanical engineering at the University of Ottawa. He has an 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. Rayan Slim and Jad Slim own a joint business in Canada.

Amer is 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, he has always looked for ways to use the power of AI to create practical solutions that revolutionize the way we live. He aims to make artificial intelligence more accessible to all students, no matter the skill level!