Deep Learning for Computer Vision

In this course you will learn to make use of Python programming language and Keras library to solve real world computer vision problems. You will learn how to apply deep learning to classify handwritten digits and work on CIFAR-10 dataset, tackle object recognition problems and more. You will also have the chance to apply CNN architectures like ResNet, GoogLeNet, Faster-RCNN and more.

Curriculum

  1. Image fundamentals
  2. Overview of Neural Networks
  3. Introduction to CNNs
  4. Optimization and Regularization
  5. CNN architectures
  6. Classification
  7. Object recognition
  8. Unsupervised Learning

Prerequisites

  • Basic knowledge of Python
  • Probability theory and calculus
  • Basic understanding of Statistical Learning
  • Knowledge of Keras and OpenCV is a plus
  • Knowledge of Neural Networks

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