Internship on Deep Learning using Matlab – NITK STEP
Designed suitably with inputs from Academic personnel’s, this specific internship program on deep learning using CNN and Matlab is floated with an Industrial point of view. This training program is designed in a way with a mix of 80% Hands on Sessions & subsequent theory sessions to cater to the industrial requirements and make the candidates industry ready.
Upon successful completion of the Internship program, the candidate will
- Have Adept knowledge of Image Processing and Deep Learning Concepts
- Be able to acquire vast Matlab Programming
- Have definite knowledge on Matlab toolboxes and the image processing techniques
- Gain a deep thrust to the Deep Learning Algorithms – Program specific & from the coding point
- Have a better understanding on the Interfacing of Peripherals & Sensors to the Controllers
- Work on the Projects – Acquire Practical Knowledge and Industry Demands
What’s more? The Candidate will be Industry Ready!
Week 1: Matlab Programming (Hands on Session)
- Overview of Matlab and the toolboxes
- Entering commands and creating variables
- Visualizing Vector & Matrix Data
- Working With Data Files & Types
- Automating Commands And Scripts
- Programming Branching & Loops
- Importing , Exporting and Visualizing images
- Image Transformations
- Type Conversions
- Contrast Adjustment and Zooming & Pixel Info Analysis
Week 2: Image Processing and Algorithms
- Plane separation
- RGB2GRAY Conversion
- Image Pixel By Pixel Accessing
- Image Black and White Conversion
- Image Weight Analysis –Histogram
- Segmenting with histogram
- Image Enhancement with Equalization
- Histogram based Segmentation
- Colour image Segmentation
Week 3: Neural Networks using Matlab
- Neural Network Concepts
- Mathematical Expression of Neural Network
- Algorithms in Machine Learning
- Limitation of Machine Learning
- Introduction and difference between Supervised and Unsupervised Learning concepts in Machine Learning
- Unsupervised Learning Algorithm-Clustering concepts, Supervised Learning Methods-Linear Regression, Logistic Regression
- Difference between Machine Learning and Deep Learning
Week 4: CNN Implementation using Matlab
- Layers in Deep Learning, Concepts of weights, bias, and activation function
- Sigmoid Function, Cost Function Formation
- NN Tool, Linear Regression App Tool, Deep Learning Toolbox
- CNN Architecture
- Applications of Deep Learning
- Assignment 1: Image Segmentation
- Assignment 2 : Edge Detection
- Assignment 3: GUI Development
- Assignment 4: Image Classification.
- Project 1: Character Recognition.
- Project 2: Disease Classification.
Industrial Internship Pedagogy
The Industrial Internship 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.
Industry Internship Benefits
- Certificate of Industry Internship Completion by STEP NITK , IEEE & PANTECH
- Proctored Assignments & Tasks validated by STEP NIT & PANTECH
- Interactive Live Session
- Mentor Access to Clarify your Queries
- Access to Recorded Video of the Sessions , Codes & PPTs
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Duration 40 Hours
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