The Math of Machine Learning – Berkeley University Textbook
This document is an attempt to provide a summary of the mathematical background needed for an introductory class in machine learning, which at UC Berkeley is known as CS 189/289A.
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Machine Learning: Functional Trees
The generalization ability of a learning algorithm depends on the appropriateness of its representation language to express a generalization of the examples for the given task. Different learning algorithms employ different representations, search heuristics, evaluation functions, and search spaces.
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Bayesian Reasoning and Machine Learning
The book is designed to appeal to students with only a modest mathematical background in undergraduate calculus and linear algebra. No formal computer science or statistical background is required to follow the book, although a basic familiarity with probability, calculus and linear algebra would be useful.
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Gaussian Processes for Machine Learning
In this book we will be concerned with supervised learning, which is the problem of learning input-output mappings from empirical data (the training dataset). Depending on the characteristics of the output, this problem is known as either regression, for continuous outputs, or classification, when outputs are discrete.
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136 Free Scientific Articles, Thesis and Reports on Deep Learning for Music
Over the last several years, a new area of research called deep learning has taken the machine learning community by storm, delivering very promising results in all areas of speech and image recognition. However, one missing link is the lack of an accessible and easy-to-use open-source deep learning library for the music and/or audio research community. In this post we will introduce you to scientific articles, thesis and reports that use deep learning approaches applied to music. The documents are generally in PDF formats, sorted by years and paired with source codes if they’re available.
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293 Free Mathematics Ebooks, Learning Platforms, Tools and Resources
This post will further your knowledge in areas that all mathematicians will be interested in. Find out what resources you can read to learn more, and find a selection of useful links including a variety of ebooks, learning platforms, videos, tools and lecture notes on a wide array of topics, such as doing math foundation, set theory, logic, type theory, algebra and many many more.
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36 Free Online Learning Resources and Platforms
Stuck at home and eager to learn something new? The good news is there are plenty of reputable places to educate yourself online for free, and here’s a good 36 of them to get you started. Our list of free online learning platforms offer classes you can take now from anywhere you wish at anytime you choose. The topics include Data Science, Classical Machine Learning, Computer Vision, Deep Learning, Natural Language Processing, Reinforcement Learning, Finance, Economics, Investing, Personal Finance and many more.
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Deep Learning
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.
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