Design for Hackers is a book that teaches the principles of good visual design to programmers, developers, and makers of any kind. It debuted at #18 on all of Amazon. Each email from our 12-week course is based upon a chapter of Design for Hackers. Buy Design for Hackers to learn along with the course...

Learn from some of the best investigative journalism instructors in the United States. This massive open course is entirely online. Anyone from anywhere in the world can take this MOOC for free. The course opens on May 12, 2014 and ends June 15, 2014. It aims to provide journalists, media practitioners...

Практический курс по анализу данных, включающий в себя максимально полезные в реальной работе знания и навыки современного специалиста в области Data Science

A koan-style tutorial in Java for Neo4j. This set of Koans provides a hands-on tutorial for learning the Neo4j open source graph database. It's part of a more comprehensive tutorial often presented by the authors and other folks. The Koan idea was borrowed from the Ruby Koans which provide a number...

The Koans walk you along the path to enlightenment in order to learn Ruby. The goal is to learn the Ruby language, syntax, structure, and some common functions and libraries. We also teach you culture. Testing is not just something we pay lip service to, but something we live. It is essential in your...

RailsCasts is produced by Ryan Bates (rbates on Twitter and ryanb on GitHub). A free episode will be released on the first Monday of each month featuring tips and tricks with Ruby on Rails. The screencasts are short and focus on one technique so you can quickly move on to applying it to your own project...

A series of sixteen lectures covering the core of the book "Information Theory, Inference, and Learning Algorithms (Cambridge University Press, 2003)" which can be bought at Amazon, and is available free online. A subset of these lectures used to constitute a Part III Physics course at the University...

Advanced course in machine learning by world leading expert Geoffrey Hinton. Topics include: graphical models, Restricted Boltzmann machines, Object Recognition in Deep Neural Nets, Recurrent neural networks, Non-linear Dimensionality Reduction and more.

Introductory course in machine learning by world leading expert Geoffrey Hinton. Topics include: linear regression and classification, neural networks, clustering, decision trees, gaussian processes, deep belief nets and more

This tutorial will look at how deep learning methods can be applied to problems in computer vision, most notably object recognition. It will start by motivating the need to learn features, rather than hand-craft them. It will then introduce several basic architectures, explaining how they learn features...

Developing high quality distributed systems software is hard; developing high quality reusable distributed systems software is even harder. The principles, methods, and skills required to develop reusable software cannot be learned by generalities. Instead, developers must learn through experience how...

Lectures from the NYU Course on Deep Learning (Spring 2014) This is a graduate course on deep learning, one of the hottest topics in machine learning and AI at the moment. In the last two or three years, Deep learning has revolutionized speech recognition and image recognition. Deep learning is...

Modern theoretical methods used in study of molecular structure, bonding, and reactivity. Concepts and practical applications. Semiempirical, ab initio, and density functional calculations of molecular electronic structure. Theoretical determination of molecular structure and spectra; relationship to...

The C++ Grandmaster Certification is an online course in which participants develop their own complete standalone C++ toolchain - including a preprocessor, compiler, assembler, linker, and standard library. The toolchain will produce executable applications for a target of (a) the Linux operating...

This is an introductory course by Caltech Professor Yaser Abu-Mostafa on machine learning that covers the basic theory, algorithms, and applications. Machine learning (ML) enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML techniques...

Лекции: - Построение суффиксного дерева (по Укконену) - Преобразование Берроуза-Вилера - Архитектура поисковых систем. Pagerank - Структура сложных сетей - Введение в байесовские сети - Автоматическая классификация текстов - Метод опорных векторов (Support vector machines) - Семантический Ве...

Haskell is a high-level, pure functional programming language with a strong static type system and elegant mathematical underpinnings, and is being increasingly used in industry by organizations such as Facebook, AT&T, and NASA. In the first 3/4 of the course, we will explore the joys of pure, lazy,...

Machine learning is a powerful set of techniques that allow computers to learn from data rather than having a human expert program a behavior by hand. Neural networks are a class of machine learning algorithm originally inspired by the brain, but which have recently have seen a lot of success at practical...

These are the videos I use to teach my Neural networks class at Université de Sherbrooke

Deep Reinforcement Learning