Computer Vision and Deep Learning A-Z: Opencv Pytorch python

Become a Master in all latest Computer Vision tools and technique. Build the powerfull apps in computer vision.

What you’ll learn

What you’ll learn

  • One who want to start their carrier in computer vision..
  • Students in college who want to get a jump start on their computer vision research.
  • Anyone interested in using Deep Learning for Computer Vision should join on..
  • Software developers and engineers that wish to learn more about computer vision.

Course Content

  • Introduction to Images –> 5 lectures • 14min.
  • Basic Image Processing Operations –> 4 lectures • 16min.
  • Image Similarity Calculation –> 1 lecture • 6min.
  • Morphological image processing –> 1 lecture • 6min.
  • Object Detecting and tracking –> 4 lectures • 17min.

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Requirements

  • Must know basic python.

What you’ll learn

This new era is being revolutionized by computer you can see around yourself and have a look. How fast the things are changing I am here to tech you the computer vision from very basic to very advance. This journey will be mostly project basis. I mean that we will learn the concept and will see how to utilize these concept to build the amazing application.

As an instructor I want you to write the code buy your self rather than copy paste from the given one this will give you addition confidence in writing the code.

In this course we will work on things are remote heart rate measurement, iris tracking, sudoko solver, Face-recognition system, ANPR(Automatic number-plate recognition) I will try my best to cover most of the technique we can use to solve the given problem and your suggestions will be always welcomed you me.

We will also cover the deep Learning and machine learning to solve the given problem.

Are there any course requirements or prerequisites?

  • Must know basic python

Who this course is for:

  • If you want to learn more about Computer Vision and Deep Learning, Or are you already a seasoned pro. Regardless of your skill level.

Amar Jeet Kushwaha

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