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 machine learning, artificial intelligence, deep learning etc…Other than learning, this program also provides an industrial exposure of working in these software’s and packages with its relevant application.
Technologies and Tools Covered
- Image processing
- Machine Learning
- Deep learning
- MATLAB programming
Introduction to the Concept of MATLAB and image processing will be dealt with. Simple programs shall be done by the participants. This shall serve as the first step into the entry to the advanced concepts implementation using MATLAB
|1||Introduction to Deep learning|
|2||MATLAB — Introduction
· MATLAB Strings
· String Subscript and String slicing
· If, For, While statements
· While and else clause on loop
· Break, continue and pass statement
|3|| MATLAB on imaging
· IMAGE PROCESSING library intro
· Importing , Exporting and Visualizing images
· Image Transformations
· Type Conversions
· Contrast Adjustment and Zooming & Pixel Info Analysis
Placing Lines Circles Texts In a Image
· Image Plane Separation
· Image Gray and B&W
· HSV Conversions
Image block separation and fixing
· Types of Noises in a Image
· Blur in images
· Median Filtering on noise removal
· Image Contour detection
· Accessing Video and Storing
· Accessing camera and storing
· HSV Conversion based color detection
· Remote camera accessing
II. Machine Learning
Machine learning brings together computer science and statistics to harness that predictive power. It’s a must-have skill for all aspiring data analysts and data scientists, or anyone else who wants to wrestle all that raw data into refined trends and predictions.
|1||Machine learning on image processing – an intro
· Training Dataset.
· Testing dataset.
· Algorithms in ML
|2.||Face recognition in real time
· Face detection
· Dataset Creation
· Testing data
· DRLBP pattern recognition
|3.||Types of Unsupervised Learning|
|4.||Supervised Learning Methods-Linear Regression, Logistic Regression|
|5.||K-Nearest Neighbors Algorithm on image|
|6.||Concept and Working Principle of SVM|
|7.||Introduction to algorithms|
III. Neural Network
Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network.
|1.||Description and working of Artificial Neural Network|
|2.||Description and working of Convolutional Neural Network|
|3.||Description and working of Back Propagation Neural Network|
Projects & Assignments
Assignment 1: Image Transformations
Assignment 2: HSV Conversion based color detection
Assignment 3: Face detection
The Program is mix of Theory sessions, Quizzes, Hands on Sessions, Liver Interaction with Experts, Assignments and Practical Exercises. Maximum Impetus is given to Hands on Sessions so as to enable the participants with the maximum knowledge transfer and satisfaction. The ratio of the theory, practical sessions will be 30:70.
· Code with Explanations
Learn everything about neural networks, with a well-structured curriculum & detailed explanations with code.
Work on various assignments which will be graded by our Trainer.
Solve real world problems as part of projects and receive valuable feedback from our trainer.
Upon Successful Completion of the Program
Upon completion of the program, the participant will have an in-depth insight into the MATLAB Programming, Neural network application. The participants will be able to program the controller and develop basic / complex applications on his own, thus making the objective of the training program as desired.
Participants also will have access to our TECHNICAL FORUM, thus getting their doubts clarified even after the session is complete. Certificates will be provided upon request.