Workshop on Statistical and Machine Learning Techniques 2024
Event Snapshot
30th - 31st May 2024
Erode, Tamil Nadu
Workshop
Venue/Offline Mode
Kongu Engineering College
About Event
OBJECTIVE
This workshop will help the participants understand principles of machine learning and how statistics is crucial while developing machine learning models. At the end of this workshop, participants will be able to get an understanding about how statistical machine learning can help in making better/informed decisions and deploy ML models.. The aim of this workshop is integrating machine learning into academic research can facilitate interdisciplinary collaborations, broaden the scope of inquiries, and contribute to pushing the frontiers of knowledge.
COURSE CONTENTS
Introduction to Machine Learning
• Introduction to machine learning: supervised vs. unsupervised learning
• Linear models (including linear regression and logistic regression)
• Loss functions and optimization Model Selection
• Cross-validation
• The bias-variance tradeoff
• High-dimensional variable selection
• Regularization methods (lasso and ridge regression) Non-linear Methods & Deep Learning
• Support vector machines
• Decision trees
• Random forests
• Neural networks
• Deep learning
Events
OBJECTIVE
This workshop will help the participants understand principles of machine learning and how statistics is crucial while developing machine learning models. At the end of this workshop, participants will be able to get an understanding about how statistical machine learning can help in making better/informed decisions and deploy ML models.. The aim of this workshop is integrating machine learning into academic research can facilitate interdisciplinary collaborations, broaden the scope of inquiries, and contribute to pushing the frontiers of knowledge.
COURSE CONTENTS
Introduction to Machine Learning
• Introduction to machine learning: supervised vs. unsupervised learning
• Linear models (including linear regression and logistic regression)
• Loss functions and optimization Model Selection
• Cross-validation
• The bias-variance tradeoff
• High-dimensional variable selection
• Regularization methods (lasso and ridge regression) Non-linear Methods & Deep Learning
• Support vector machines
• Decision trees
• Random forests
• Neural networks
• Deep learning
Workshops
OBJECTIVE
This workshop will help the participants understand principles of machine learning and how statistics is crucial while developing machine learning models. At the end of this workshop, participants will be able to get an understanding about how statistical machine learning can help in making better/informed decisions and deploy ML models.. The aim of this workshop is integrating machine learning into academic research can facilitate interdisciplinary collaborations, broaden the scope of inquiries, and contribute to pushing the frontiers of knowledge.
COURSE CONTENTS
Introduction to Machine Learning
• Introduction to machine learning: supervised vs. unsupervised learning
• Linear models (including linear regression and logistic regression)
• Loss functions and optimization Model Selection
• Cross-validation
• The bias-variance tradeoff
• High-dimensional variable selection
• Regularization methods (lasso and ridge regression) Non-linear Methods & Deep Learning
• Support vector machines
• Decision trees
• Random forests
• Neural networks
• Deep learning
Who Can Attend:
CSE ECE IT EEE Chemical Industrial MCA Telecommunication Aeronautical AerospaceAccommodation
Accommodation and boarding if required will be provided in the college campus on chargeable basis.
How to reach Kongu Engineering College, Erode
Perundurai, Erode-638 052, Tamilnadu, India
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