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Lecture 1 | Machine Learning (Stanford)

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 provides a broad introduction to machine learning and statistical pattern recognition. Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed. Complete Playlist for the Course: www.youtube.com CS 229 Course Website: www.stanford.edu Stanford University: www.stanford.edu Stanford University Channel on YouTube: www.youtube.com
Категория: Education
Время: 00:51:30
Теги: science math engineering computer technology robotics reinforcement supervised learning algorithm machine image processing ICA theory programming code
 

Lecture 2 | Machine Learning (Stanford)

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 discusses how they relate to machine learning. This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed. Complete Playlist for the Course: www.youtube.com CCS 229 Course Website: www.stanford.edu Stanford University: www.stanford.edu Stanford University Channel on YouTube: www.youtube.com
Категория: Education
Время: 00:57:12
Теги: science math engineering computer technology robotics algebra linear regression learning algorithm gradient descent normal equation
 

Machine Learning: About the class

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
Категория: Education
Время: 00:01:29.250
Теги: machine learning Stanford Andrew Ng free educational intro University school AI students class
 

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

(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 intelligence could result one day in a robot that can clean your house. STAN: Society, Technology, Art and Nature, was Stanford University's prototype conferecne for TEDxStanford, and showcased some of the university's top faculty, students, alumni and performers in an intense four-hour event laced with surprising appearances and memorable experiences. STAN, modeled after TED, explored big questions about society, technology, art and nature in a format that invites feedback and engagement. Stanford University: www.stanford.edu STAN 2011: stan2011.stanford.edu Andrew Ng ai.stanford.edu Stanford University Channel on YouTube: www.youtube.com
Категория: Education
Время: 00:12:20.250
Теги: robots artificial intelligence machine learning computer science Andrew Ng Stanford STAN tedx TED autonomous helicopter personal robotics singularity conference
 

Machine Learning and Intelligence in Our Midst

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 developments have come together to create a nurturing environment for developing and fielding applications of machine learning and reasoning--and for harnessing machine intelligence to provide value to businesses and to people in the course of their daily lives. Key advances include jumps in the availability of rich streams of data, precipitous drops in the cost of storing and retrieving large amounts of data, increases in computing power and memory, and jumps in the prowess of methods for performing machine learning and reasoning. The combination of these advances have created an inflection point in our ability to harness data to generate insights and to guide decision-making. This talk will present recent efforts on learning and inference, highlighting key ideas in the context of applications, including advances in transportation and health care, and the development of new types of applications and services. Opportunities for creating systems with new kinds of competencies by weaving together multiple data sources and models will also be discussed.
Категория: Science & Technology
Время: 00:39:00
Теги: Microsoft MSR Machine Learning Future Microsoft Research Techfest techfest 2012 Software Technology Big Data Eric Horvitz
 

Practical Machine Learning in Python

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-suited to solving these particular problems, the tra
Категория: Education
Время: 00:22:11.250
Теги: psf python pycon pycon2012 pycon_2012 mattspitz
 

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

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 well as walk you through a few exorcises that demonstrate how you can use machine learning technology. **More tutorials on open source development at marakana.com
Категория: Science & Technology
Время: 00:56:30.750
Теги: Jacob vanderplas Machine Learning pydata Python scikit-learn tutorial demo example marakana techtv
 

Lecture 3 | Machine Learning (Stanford)

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 logistic regression and how it relates to machine learning. This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed. Complete Playlist for the Course: www.youtube.com CS 229 Course Website: www.stanford.edu Stanford University: www.stanford.edu Stanford University Channel on YouTube: www.youtube.com
Категория: Education
Время: 00:54:55.500
Теги: 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)

Категория: Education
Время: 00:06:23.250
Теги: machine learning introduction data mining VS machine learning
 

Scala and Machine Learning with Andrew McCallum

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 Odersky didn't initially expect Scala to find a following in the field of machine learning because of machine learning's large appetite for memory and numeric computation. But the field is expanding in new ways, with interest in parallel and distributed computation, dynamically changing model structures, and the desire to put easy-to-use DSLs into the hands of non-experts. This talk will describe these trends and discuss several machine learning projects that use Scala, including FACTORIE, a 30k-line DSL for graphical models whose development is being sponsored by Google and the NSF.
Категория: Science & Technology
Время: 00:23:57.750
Теги: Andrew mccallum Scala and Machine Learning DSL FACTORIE Northeast Symposium nescala Marakana techtv
 
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