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- 6.867 Machine Learning
ai.mit.edu/courses/6.867-f04/lectures.html

Mon 9/20||Lecture 4: statistical regression, uncertainty, active learning| Wed 9/29||Lecture 7: support vector machines, kernels||Notes on Lagrange multipliers (postscript)| Mon 10/25||Lecture 12: VC-bounds, structural risk minimization, compression and mod.. - Machine Learning -- Introduction - Math Programming
jeremykun.com/2012/08/04/machine-learning-introduction

Aug 2012 - While we do intend to cover the classical topics of machine learning, such as neural networks and decision trees, we would like to quickly approach more sophisticated modern techniques such as support vector machines and methods based on Kolmogorov complexi.. - Machine Learning for Hackers [Book]
oreilly.com/library/view/machine-learning-for/9781449330514

If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help.. - Machine Learning of Sets
akosiorek.github.io/ml/2020/08/12/machine_learning_of_sets.html

Aug 2020 - where \(p_c(k)\) is the probability mass function of the set size, \(k!\) accounts for all possible permutations of set elements \(\mathbf{x}_i\), \(U \in \mathbb{R}_+\) is the unit volume expressed as a scalar value, and \(f_k\) is the permutation-invarian.. - Machine Learning and Python
web.archive.org/web/20150919005750/sebastianraschka.com/blog/2015/why-python.html

Sep 2015 - If you are part of the software engineering team that wants to optimize the next game-changing high-frequency trading model from your machine learning and data science division, Python is probably not for you (but maybe it was the language of choice by the .. - Test-First Machine Learning | codingossip
web.archive.org/web/20200804203352/codingossip.github.io/2020/test-first-machine-learning

Aug 2020 - When values are mocked, success conditions are defined and tests are running, it’s time to show that the ML model under testing is training and performing predictions. As in traditional software engineering, testing precise execution behavior, timing or per.. - Introduction to Machine Learning Course
udacity.com/course/intro-to-machine-learning--ud120

It will teach you how to extract and identify useful features that best represent your data, a few of the most important machine learning algorithms, and how to evaluate the performance of your machine learning algorithms. We’ll bring machine learning to li.. - Machine Learning in Javascript: Introduction
burakkanber.com/blog/machine-learning-in-other-languages-introduction

It's possible to get excellent performance out of ML algorithms in languages like PHP and Javascript. I advocate writing ML algorithms in other languages because the practice of writing ML algorithms from scratch helps you learn them fundamentally, and it a.. - The Mechanics of Machine LearningWarning: The content of this book is so unexciting that you'll be able to use it in your actual job! You'll learn how machine learning works and how to apply it in practice. We focus on just a few powerful models (algorithms) that are extremely effective on..
- Machine Learning cheat sheet | Home of Emanuel Ferm
web.archive.org/web/20110506172336/eferm.com/machine-learning-cheat-sheet

May 2011 - For a recently taken course in Machine Learning, a substantial part involved learning and applying linear classifiers and clustering algorithms on smaller data sets. I figured someone else might appreciate it as well, so why not make it available for more p..