Why this course?

Description

Internship on Deep Learning Masterclass

About the Program
This program has been initiated to enhance the knowledge from beginner to advance for the people who are interested in learning of advanced technologies like Deep Learning, Artificial intelligence etc... Other than learning, this program also provides an industrial exposure of working in this software and the toolbox with its relevant Algorithms. This program provides a comprehensive introduction to practical deep learning using MATLAB. In this hands-on program you will learn how to perform deep learning Algorithms using MATLAB. Also, you will learn the fundamentals of deep learning and understand terms like “layers”, “networks”, and “loss” functions. Internship on Deep Learning

Technologies and Tools Covered
 MATLAB
 Image Processing
 Neural Network

 

LEARNING PATH
I. Basics of AI & Introduction
This session will encourage to learn what AI is, what can be done with AI, and how to start creating AI methods. The combination of theory with practical exercises will be conduct.

1. Introduction of Artificial Intelligence
2. Process flow for an AI
3. Deep Learning Introduction
4. MATLAB Introduction
5. Image Processing Overview

 

II. Image Processing in Machine Learning & Deep Learning
Introduction to the concepts of Image processing in MATLAB will be dealt with simple programs by the participants. This shall serve as the first step into the advanced concepts implementation in Deep Learning by using MATLAB.

1. Image Processing Using MATLAB
2. Neural Network Concepts
3. Mathematical Expression of Neural Network
4. Algorithms in Machine Learning
5. Limitation of Machine Learning

 

III. Deep Learning Concepts
Here you’ll learn more about the actual algorithms that make creating AI methods possible. Some basic programming skills are recommended to get the most out of the course. Also, you will learn the fundamentals of deep learning and understand terms like “layers”, “networks”, and “loss” functions.

1 Introduction to Deep Learning
2 CNN Architecture
3 Applications of Deep Learning

 

Projects & Assignments
Practical 1: Image Pre-processing & Applying Transformation
Practical 2: Image Segmentation
Practical 3: Edge Detection
Practical 4: GUI Development
Practical 5: Image Classification.

Project 1: Character Recognition.
Project 2: Disease Classification.
Project 3: Neural Network Algorithms & Application