Deep Learning in Computer Vision

Kalyan Chary · September 26, 2021

About this Course

Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars.

The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and often demonstrated in movies and TV-shows example of computer vision and AI.

What you’ll learn

  • Using Latest Tools & Techniques in Deep Learning & Computer Vision
  • Learning how to used the latest Tensorflow 2.0
  • How to apply Transfer Learning, Ensemble Learning, using GPUs & TPUs
  • How to work & win Kaggle Competitions
  • Learning to use FastAI
  • How to use Generative Adversarial Networks
  • How to use Weights & Biases for recording Experiments
  • Learning to use Detectron2 for Object Detection
  • Making Machine Learning Web Application from Scratch
  • Learn how to use OpenCV for Computer Vision
  • How to make Real World Applications & Deploy into Cloud
  • Learning Techniques like Object Detection, Classification & Generation
  • Learning how to use Heroku for deploying ML models
  • Working on Kaggle Competitions & Kaggle Kernels
  • Exploring & Visualizing Datasets using popular libraries like Matplotlib & Plotly.
  • Learinng how to use libraries like Pandas, Sklearn, Numpy
  • Creating Advance Data Pipelines using Tensorflow for training Deep Learning Models
  • Setting up Environment & Project for Deep Learning & Computer Vision

Course Content

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About Instructor

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or $ 15000

Course Includes

  • 10 Lessons
  • 55 Topics