Objective :
The objective of the course is to teach the basic fundamentals of machine learning , algebraic and geometric interpretation of data, density estimation based supervised learning models and other related topics. This ends with deep learning and its applications in image processing. This will surely help post graduate students and researchers discover patterns and solve research problems.
Program Schedule
| 9.00 am – 9.30 am | 9.30 am – 11.00 am | 11.00 am – 11.15 am | 11.15 am – 1:00 pm | 1.00 pm – 2:00 pm | 2.00 pm – 3:30 pm | 3.30 pm – 3:45 pm | 3.45 pm – 4:30 pm | |
| Dec 10, 2018 | Amriteshwari Hall | Shraddha Hall | Tea break
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Shraddha Hall | Lunch Break
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CAD Lab | Tea Break
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CAD Lab |
| Inauguration | Introduction to ML | Mathematical Foundations and Geometric Interpretation for ML |
Lab Session- Python for ML | Sentiment Analysis | ||||
| Dr. V. Sugumaran (VIT, Chennai) |
Dr. Manju B.R. | Dr. Sajeev | Ms. Thara S. | |||||
| Dec 11, 2018 | 9.00 am -11.00 am | 11.15 am – 1 pm | 2.00 pm – 3.30pm | 3.45 pm – 4.30 pm | ||||
| Shraddha Hall | Shraddha Hall | CAD Lab | CAD Lab | |||||
| Predictive Modelling | Discriminative Supervised Learning Models | Lab Session- Exploratory Data Analysis | Graph Mining | |||||
| Dr. Manju B.R. | Ms. Sandhya Harikumar | Ms. Gayathri R.G. | Ms. Gayathri R.G. | |||||
| Dec 12, 2018 | 9.00 am -11.00 am | 11.15 am – 1 pm | 2.00 pm – 3.30pm | 3.45 pm – 4.30 pm | ||||
| ML-a probabilistic perspective | Generative Supervised Learning Models | Lab Session-Supervised Learning Models | Complex Networks | |||||
| Dr. Manju B.R. | Ms. Sandhya Harikumar | Ms. Geetha M. | Mr. Jo Cheriyan | |||||
| Dec 13, 2018 | 9.00 am -11.00 am | 11.15 am – 1 pm | 2.00 pm – 3.30 pm | 3.45 pm – 4.30 pm | ||||
| Matrix factorization for Unsupervised Learning | Ensemble Models | Lab Session-Unsupervised Models/ Ensemble Models | Task Recommendation in Crowdsourcing Systems | |||||
| Ms. Sandhya Harikumar | Dr. Vivek Menon | Ms. Ramya Rajesh, Dr. Vivek Menon | Ms. Aishwarya Kurup | |||||
| Dec 14, 2018 | 9.00 -11.00 am | 11.15 am – 1 pm | 2.00 pm – 3.00 pm | 3:00 pm – 3:15 pm | 3.15 pm – 4.00 pm | |||
| Shraddha Hall | Shraddha Hall | CAD Lab | Amritesh | |||||
| Introduction to Deep Learning | Deep Learning Case Studies | Lab Session -Tensor Flow | Tea Break
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Valedictory Function
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| Dr. Deepak Mishra(IIST, Trivandrum)
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Dr. Deepak Mishra/Dr. Gopakumar | Dr. Gopakumar | ||||||
