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Components of the learning problem. Lecture 1 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser ...

Introduction to Gaussian process regression. Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html Course ...

SYDE 522 – Machine Intelligence (Winter 2019, University of Waterloo) Target Audience: Senior Undergraduate Engineering ...

Bayesian optimization, Thompson sampling and multi-armed bandits. Applications to algorithm configuration, intelligent user ...

Machine learning is all around us; on our phones, powering social networks, helping the police and doctors, scientists and mayors ...

Data is one of the main factors determining whether machine learning projects will succeed or fail. That's why it is necessary to ...

A quick introduction to PAC Learning and VC Dimension.

There's one specific role that builds a bridge between data science and its practical counterpart, machine learning. Meet the ...

In which we discuss an introduction to computational topology, the utility of Betti numbers, simplicial homology (with examples) ...

With recent computational advances, our ability to create novel machine learning models is far outpacing our capabilities for ...

Maximum likelihood and linear regression. Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html Course taught ...

Lecture 11 in the Introduction to Machine Learning (aka Machine Learning I) course by Dmitry Kobak, Winter Term 2020/21 at the ...

Fundamentals of Machine Learning for Earth Science Part 1: Overview of Machine Learning Trainers: Jordan A. Caraballo-Vega, ...

... Machine Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd9bPcq0fj91Jgk_-h1H_W3V ⭕ Coding Machine Learning: ...

Introduction to Random Forests. Welcome to Introduction to Machine Learning for Coders! Lesson 1 will show you how to create a ...

... for machine learning fundamentals - https://www.youtube.com/playlist?list=PL-9_KFQd8ssLS8TV5-GsYhp6fgZ3gZM_a Discord ...

This video introduces unsupervised learning, supervised learning, and core data structures used in machine learning. The slides ...

Some parametric methods, like polynomial regression and Support Vector Machines stand out as being very versatile. This is due ...

SYDE 522 – Machine Intelligence (Winter 2019, University of Waterloo) Target Audience: Senior Undergraduate Engineering ...

Decision trees for classification. Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html Course taught in 2013 at ...