A short course introducing the main ideas and algorithms of Machine Learning. The goal of the course is to cover the topics at a high level so that it would act as a first course for a full fledged Machine Learning course. The course will be delivered in spoken Tamil while the technical terms discussed/exams/assignments will be in English.Intended Audience: Native Tamil speaking audience (Teachers/ Undergraduate Students)Pre-Requisites: A basic course in linear algebra/probability/programming/algorithms would be a big plus. These are not strong pre-requisites.Industry Support: All Data centric companies including those that have core business in search/e-commerce/social-media
Overview
Syllabus
Week 1: Introduction to Supervised Learning - Regression; Topics - Linear Regression; Ridge Regression; LASSO;
Week 2:Supervised Learning - Classification; Topics: K-NN, Decision Tree, Naive Bayes, Logistic Regression
Week 3:Supervised Learning - Classification; Topics: Perceptron, Support-Vector Machines, Introduction to Neural Networks
Week 4:Unsupervised Learning - K-means Clustering, PCA
Week 2:Supervised Learning - Classification; Topics: K-NN, Decision Tree, Naive Bayes, Logistic Regression
Week 3:Supervised Learning - Classification; Topics: Perceptron, Support-Vector Machines, Introduction to Neural Networks
Week 4:Unsupervised Learning - K-means Clustering, PCA
Taught by
Prof. Arun Rajkumar
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4.0 rating, based on 1 Class Central review
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I am Seenivasan, Asst. Professor of Annai Fathima College of Arts and Science, Madurai. In this semester i am going to handle Machine Learning Subject. "Introducing Machine Learning" effectively sets the stage for a deeper exploration into machine learning concepts. It's a promising start for beginners looking to grasp the basics and build a solid foundation in this rapidly evolving field.
