AI for Image Understanding

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AI for Image Understanding

 

Overview

Today, there is a great need for the introduction of AI intro all aspects of software, making the enterprise software smart. The argument one often finds in articles describing the unsatisfactory state of business software is, “If smartphones can do it, why can’t enterprise software?”

This course addresses the need for smart software for image understanding.

The course is intended for software architects and engineers. It gives them a practical level of experience, achieved through a combination of about 50% lecture, 50% demo work with student’s participation.

Duration:

3 Days

Audience:

Software Architects, Developers

Prerequisites:

  • familiarity with any programming language
  • be able to navigate Linux command line
  • basic knowledge of command line Linux editors (VI / nano)

Lab environment:

Working environment will be provided for students. Students would only need an SSH client and a browse.
Zero Install: There is no need to install software on students’ machines.

Course Outline

  1. AI overview
    • A brief history of AI
    • Types of AI systems
    • Training machine learning models
    • Applying models for prediction
    • Demos and Labs
  2. Image processing elements
    • Convolutions
    • Pooling
    • Edge Detection
    • De-noising
  3. Image Processing with TensorFlow and Keras
    • Google democratization of AI with TensorFlow
    • Types of neural network (Perceptron, CNN) and their use
    • Image Processing with TensorFlow
    • Use cases and labs