Course Abstract

Training duration : 60 minutes

Ever wonder how Facebook’s facial recognition or Snapchat’s filters work? Faces are a fundamental piece of photography, and building applications around them has never been easier with open-source libraries and pre-trained models. This course provides an introduction to face processing using Computer Vision models. Learners will be exposed to latest techniques used for building applications for face-detection, recognition, manipulation and classification

DIFFICULTY LEVEL: ADVANCED

Learning Objectives

  • You will understand some of the computer vision and machine learning techniques behind applications Snapchat filter and Facebook facial recognition.

  • Develop your own prototypes to tackle tasks such as:

  • Face detection (e.g. digital cameras),

  • Recognition (e.g. Facebook Photos),

  • Classification (e.g. identifying emotions),

  • Manipulation (e.g. Snapchat filters), and more.

Instructor

Instructor Bio:

Background knowledge

  • This course is for current or aspiring Data Scientists, Computer & Machine Learning Engineers, Deep Learning Engineers, AI Product Managers

  • Knowledge of following tools and concepts is useful:

  • Workings of Deep Learning models. Please refer the "Deep Learning with Tensorflow & PyTorch" course by Dr. Jon Krohn in course library.

  • Some familiarity with Computer Vision concepts

  • Good foundation of mathematics for data science

Real-world applications

  • Snapchat smart filters use face processing with Computer Vision

  • Face recognition systems are being widely used in digital banking, self-driving cars and various other mobile apps