ankitbit / Machine-Learning

This repository corresponds to the course "Machine Learning" taught at the Faculty of Informatics (FIB), UPC under the MIRI-Data Science Program

Machine Learning

Official Website

KNN

• Lecture 1 : Introduction to Machine Learning
• Lecture 2 : Theoretical Issues in Machine Learning and Regression Analysis
• Lecture 3 : Linear Regression and Beyond
• Lecture 4 : Bayesian Decision Theory and Classification
• Lecture 5 : Generative Bayesian Classifiers: K-Nearest neighbours, Naive bayes, LDA/QDA/RDA
• Lecture 6 : Discriminative Classifiers: Logistic Regression and Beyond
• Lecture 7 : Probabilistic Clustering. Read more about the topic by accessing lectures of Unsupervised Learning
• Lecture 8: Learning with Kernels (I) : Support Vector Machines

-E Books -Must reads for data scientists

Reference Courses

• Scalable Machine Learning: Taught by Alex Smola at UC Berkley
• 10-601 : Machine Learning @ CMU-
• Machine Learning Labs and Lectures @ Smith
• Standard Deviation Blog- By David Ziganto | Special focus on ML, Deep Learning, Programming in Python, Big Data etc.
• Deeply Thought: Resources for Deep Learning, Machine Learning
• Machine Learning for Statistics: SDGB 7847- Columbia University
• Applied Machine Learning

Advanced Machine Learning

CMU Cornell Ohio: Machine Learning for Data Science Statistical Machine Learning and more courses by same author Courses Machine Learning @University of British Columbia

• Classification with Scikit Learn

• Introduction to Machine Learning (R)

Just for fun

• Shiring