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Lecture 1 | Machine Learning (Stanford)

Complete description: Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng provides an overview of the course in this introductory meeting. This course prov
Thematic Section: Education
Duration: 00:51:30
Other materials on this topic: science math engineering computer technology robotics reinforcement supervised learning algorithm machine image processing ICA theory programming code

Machine Learning and Intelligence in Our Midst

Complete description: The creation of intelligent computing systems that perceive, learn, and reason has been a long-standing and visionary goal in computer science. Over the last 20 years, technical and infrastructural de
Thematic Section: Science & Technology
Duration: 00:39:00
Other materials on this topic: Microsoft MSR Machine Learning Future Microsoft Research Techfest techfest 2012 Software Technology Big Data Eric Horvitz

Machine Learning: About the class

Complete description: Stanford University will be offering a free, online machine learning class in Fall 2011, taught by Prof. Andrew Ng. Sign up at ml-class.org
Thematic Section: Education
Duration: 00:01:29.250
Other materials on this topic: machine learning Stanford Andrew Ng free educational intro University school AI students class

Lecture 2 | Machine Learning (Stanford)

Complete description: Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on linear regression, gradient descent, and normal equations and discuss
Thematic Section: Education
Duration: 00:57:12
Other materials on this topic: science math engineering computer technology robotics algebra linear regression learning algorithm gradient descent normal equation

Practical Machine Learning in Python

Complete description: Matt Spitz There are a plethora of options when it comes to deciding how to add a machine learning component to your python application. In this talk, I'll discuss why python as a language is well-sui
Thematic Section: Education
Duration: 00:22:11.250
Other materials on this topic: psf python pycon pycon2012 pycon_2012 mattspitz

The Future of Robotics and Artificial Intelligence (Andrew Ng, Stanford University, STAN 2011)

Complete description: (May 21, 2011) Andrew Ng (Stanford University) is building robots to improve the lives of millions. From autonomous helicopters to robotic perception, Ng's research in machine learning and artificial
Thematic Section: Education
Duration: 00:12:20.250
Other materials on this topic: robots artificial intelligence machine learning computer science Andrew Ng Stanford STAN tedx TED autonomous helicopter personal robotics singularity conference

Tutorial: scikit-learn - Machine Learning in Python with Contributor Jake VanderPlas

Complete description: In this video tutorial from PyData Workshop, Jacob VanderPlas is going to give you an overview of machine learning in Python using scikit-learn. He'll talk about general machine learning concepts, as
Thematic Section: Science & Technology
Duration: 00:56:30.750
Other materials on this topic: Jacob vanderplas Machine Learning pydata Python scikit-learn tutorial demo example marakana techtv

Lecture 3 | Machine Learning (Stanford)

Complete description: Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng delves into locally weighted regression, probabilistic interpretation and logisti
Thematic Section: Education
Duration: 00:54:55.500
Other materials on this topic: science math engineering computer technology robotics algebra locally weighted logistic regression linear probabilistic interpretation Gaussian distribution digression perceptron

Machine Learning (Introduction + Data Mining VS ML)

Complete description:
Thematic Section: Education
Duration: 00:06:23.250
Other materials on this topic: machine learning introduction data mining VS machine learning

Scala and Machine Learning with Andrew McCallum

Complete description: In this video from the Northeast Scala Symposium, Andrew McCallum, Professor of Computer Science at University of Massachusetts Amherst, is going discuss trends in machine learning using Scala. Martin
Thematic Section: Science & Technology
Duration: 00:23:57.750
Other materials on this topic: Andrew mccallum Scala and Machine Learning DSL FACTORIE Northeast Symposium nescala Marakana techtv

Machine Learning in Ecological Science and Environmental Management

Complete description: SPEAKER & AFFILIATION: Thomas G. Dietterich, Oregon State University Corvalis DESCRIPTION: This lecture has been videocast from the Computer Science Department at Duke U. The abstract of this lecture
Thematic Section: Science & Technology
Duration: 00:50:16.500
Other materials on this topic: Triangle Computer Science Distinguished Lecture Seminar Colloquium Machine Learning Ecological Environmental Management Research Triangle

Machines Can Learn

Complete description: ai-one's Topic-Mapper API enables programmers to build machine learning into applications. ai-one has discovered a new form of artificial intelligence that detects the inherent structure of data at th
Thematic Section: Science & Technology
Duration: 00:02:42
Other materials on this topic: AI ML artificial intelligence machine learning API IBM Watson

(ML 1.1) Machine learning - overview and applications

Complete description: Attempt at a definition, and some applications of machine learning. A playlist of these Machine Learning videos is available here: www.youtube.com
Thematic Section: Education
Duration: 00:06:42
Other materials on this topic: machine learning statistics math

Weka Machine Learning Tutorial 02: Explorer-Preprocess

Complete description:
Thematic Section: Education
Duration: 00:08:01.500
Other materials on this topic: Weka Machine learning explorer data mining preprocess Tutorial Weka (machine Learning) Lesson

Bay Area Vision Meeting: Unsupervised Feature Learning and Deep Learning

Complete description: Bay Area Vision Meeting (more info below) Unsupervised Feature Learning and Deep Learning Presented by Andrew Ng March 7, 2011 ABSTRACT Despite machine learning's numerous successes, applying machine
Thematic Section: Science & Technology
Duration: 00:36:07.500
Other materials on this topic: bay area vision google tech talk machine learning machine vision

Machine Learning in Science and Engineering [21C3]

Complete description: Machine Learning in Science and Engineering A Brief Introduction into Machine Learning with a few Application Examples A broad overview about the current stage of research in Machine Learning starting
Thematic Section: Education
Duration: 00:41:45
Other materials on this topic: CCC Chaos Computer Club 21C3 Talk Lecture 2004

NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Machine Learning...

Complete description: Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Machine Learning and Hadoop by Josh Wills Abstract: We'll review common use cases for machine lea
Thematic Section: Science & Technology
Duration: 00:30:36
Other materials on this topic: bigml d2 wills

[PURDUE MLSS] Introduction to Machine Learning by Dale Schuurmans Part 1/6

Complete description: Lecture slides: learning.stat.purdue.edu Abstract of the talk: This course will provide a simple unified introduction to batch training algorithms for supervised, unsupervised and partially-supervised
Thematic Section: Science & Technology
Duration: 00:31:27.750
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Recommendation Engines using Machine Learning, and JRuby by Matt Kirk

Complete description: Ever wonder how netflix can predict what rating you would give to a movie? How do recommendation engines get built? Well, it's possible with JRuby and it's fairly straight forward. Many engines are bu
Thematic Section: Science & Technology
Duration: 00:21:18
Other materials on this topic: rubymidwest2011 Ruby (Programming Language)

Biologically Inspired Machine Learning

Complete description: (March 31, 2010) Venkat Rangan, a hardware engineer at Qualcomm Incorporated, discusses hardware, software, and networking challenges that humans will face in a creating a neuromorphic computer. Stanf
Thematic Section: Education
Duration: 00:44:51
Other materials on this topic: computer science technology electrical engineering research and development R&D machine learning software hardware networking brain computing power neuroscience neurons algorithms

ai-one SDK for Machine Learning Applications

Complete description: Overview of ai-one Topic-Mapper SDK for building machine learning applications with lightweight ontologies.
Thematic Section: Science & Technology
Duration: 00:06:11.250
Other materials on this topic: machine learning SDK Topic-Mapper unstructured data lightweight ontology

NIPS 2011 Music and Machine Learning Workshop: Learning from Musical Structure

Complete description: International Music and Machine Learning Workshop: Learning from Musical Structure at NIPS 2011 Invited Talk: A Topic Model for Melodic Sequences by Athina Spiliopoulou Athina is a PhD student in the
Thematic Section: Science & Technology
Duration: 00:21:42.750
Other materials on this topic: music ml 002

[PURDUE MLSS] Large-scale Machine Learning and Stochastic Algorithms by Leon Bottou (Part 1/6)

Complete description: Lecture notes: learning.stat.purdue.edu Large-scale Machine Learning and Stochastic Algorithms During the last decade, data sizes have outgrown processor speed. We are now frequently facing statistica
Thematic Section: Science & Technology
Duration: 00:46:12
Other materials on this topic: 41 bottou

IBM Watson: Computer Understands Natural Language

Complete description: IBM's Watson is a real time, natural language processing computer that employs deep analytics and machine learning capabilities to answer questions. Watson's ability will be tested on the game show Je
Thematic Section: Science & Technology
Duration: 00:00:26.250
Other materials on this topic: ibm jeopardy data mining machine learning ken jennings natural language processing predictive analytics smarter planet data analytics natural language ibm watson question answering question answering system deep analytics groucho marx marx

LSE Research: The Mathematics of Machine Learning

Complete description: Computers struggle with tasks we find simple. But try to describe explicitly the difference between the handwritten numerals 1 and 7, and you begin to appreciate the problem. Professor Martin Anthony
Thematic Section: Education
Duration: 00:04:30
Other materials on this topic: LSE London School of Economics Research mathematics machine learning PASCAL artifical intelligence AI Professor Martin Anthony

NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Big Machine Learning...

Complete description: Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Big Machine Learning made Easy by Miguel Araujo Miguel Araujo holds a BS and MS in computer scien
Thematic Section: Science & Technology
Duration: 00:20:54
Other materials on this topic: new bigml d1 araujo

Machine Learning in Support of Family Coordination

Complete description: Google Tech Talk (more info below) June 1, 2011 Presented by Scott Davidoff, Ph.D. ABSTRACT This talk describes how my work with busy families: (1) identifies how their coordination breaks down (from
Thematic Section: Science & Technology
Duration: 00:37:19.500
Other materials on this topic: google tech talk machine learning family systems

Scalable Machine Learning (CS281B) - Systems 1A

Complete description: Unedited Lectures from the CS281B class in UC Berkeley More details (slides, assignments, scribe notes) can be found at alex.smola.org
Thematic Section: Science & Technology
Duration: 00:40:43.500
Other materials on this topic: Machine Learning Systems Parallelization Distributed Hashing mapreduce Scalability

Machine Learning: What you will learn

Complete description: What you will learn in the Stanford free online machine learning class in Fall 2011. Sign up at ml-class.org
Thematic Section: Education
Duration: 00:01:43.500
Other materials on this topic: machine learning Stanford Andrew Ng free educational intro University school AI students class
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