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One of the cornerstones of the technology revolution, Stanford now offers some courses for free via distance learning. One of the more exciting courses is of course- machine learning
About The Course
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
Professor Andrew Ng is Director of the Stanford Artificial Intelligence Lab, the main AI research organization at Stanford, with 20 professors and about 150 students/post docs. At Stanford, he teaches Machine Learning, which with a typical enrollment of 350 Stanford students, is among the most popular classes on campus. His research is primarily on machine learning, artificial intelligence, and robotics, and most universities doing robotics research now do so using a software platform (ROS) from his group.
- When does the class start?The class will start in January 2012 and will last approximately ten weeks.
- What is the format of the class?The class will consist of lecture videos, which are broken into small chunks, usually between eight and twelve minutes each. Some of these may contain integrated quiz questions. There will also be standalone quizzes that are not part of video lectures, and programming assignments.
- Will the text of the lectures be available?We hope to transcribe the lectures into text to make them more accessible for those not fluent in English. Stay tuned.
- Do I need to watch the lectures live?No. You can watch the lectures at your leisure.
- Can online students ask questions and/or contact the professor?Yes, but not directly There is a Q&A forum in which students rank questions and answers, so that the most important questions and the best answers bubble to the top. Teaching staff will monitor these forums, so that important questions not answered by other students can be addressed.
- Will other Stanford resources be available to online students?No.
- How much programming background is needed for the course?The course includes programming assignments and some programming background will be helpful.
- Do I need to buy a textbook for the course?No.
- How much does it cost to take the course?Nothing: it’s free!
- Will I get university credit for taking this course?No.Interested in learning machine learning-
Well here is the website to enroll http://jan2012.ml-class.org/
Here is an interview with Zach Goldberg, who is the product manager of Google Prediction API, the next generation machine learning analytics-as-an-api service state of the art cloud computing model building browser app.
Ajay- Describe your journey in science and technology from high school to your current job at Google.
Zach- First, thanks so much for the opportunity to do this interview Ajay! My personal journey started in college where I worked at a startup named Invite Media. From there I transferred to the Associate Product Manager (APM) program at Google. The APM program is a two year rotational program. I did my first year working in display advertising. After that I rotated to work on the Prediction API.
Ajay- How does the Google Prediction API help an average business analytics customer who is already using enterprise software , servers to generate his business forecasts. How does Google Prediction API fit in or complement other APIs in the Google API suite.
Zach- The Google Prediction API is a cloud based machine learning API. We offer the ability for anybody to sign up and within a few minutes have their data uploaded to the cloud, a model built and an API to make predictions from anywhere. Traditionally the task of implementing predictive analytics inside an application required a fair amount of domain knowledge; you had to know a fair bit about machine learning to make it work. With the Google Prediction API you only need to know how to use an online REST API to get started.
Ajay- What are the additional use cases of Google Prediction API that you think traditional enterprise software in business analytics ignore, or are not so strong on. What use cases would you suggest NOT using Google Prediction API for an enterprise.
Zach- We are living in a world that is changing rapidly thanks to technology. Storing, accessing, and managing information is much easier and more affordable than it was even a few years ago. That creates exciting opportunities for companies, and we hope the Prediction API will help them derive value from their data.
The Prediction API focuses on providing predictive solutions to two types of problems: regression and classification. Businesses facing problems where there is sufficient data to describe an underlying pattern in either of these two areas can expect to derive value from using the Prediction API.
Ajay- What are your separate incentives to teach about Google APIs to academic or researchers in universities globally.
Zach- I’d refer you to our university relations page-
Google thrives on academic curiosity. While we do significant in-house research and engineering, we also maintain strong relations with leading academic institutions world-wide pursuing research in areas of common interest. As part of our mission to build the most advanced and usable methods for information access, we support university research, technological innovation and the teaching and learning experience through a variety of programs.
Ajay- What is the biggest challenge you face while communicating about Google Prediction API to traditional users of enterprise software.
Zach- Businesses often expect that implementing predictive analytics is going to be very expensive and require a lot of resources. Many have already begun investing heavily in this area. Quite often we’re faced with surprise, and even skepticism, when they see the simplicity of the Google Prediction API. We work really hard to provide a very powerful solution and take care of the complexity of building high quality models behind the scenes so businesses can focus more on building their business and less on machine learning.
I am still angry with THE netflix for 1 mill I lost out. No sweat! this time the money is 3 times as much, it is legit, and yes baby you can change the world, make it a better place and get rich.! see details below-http://www.heritagehealthprize.com/c/hhp/Data
HERITAGE HEALTH PRIZE DATA FILES
DATA FILES (CLICK TO DOWNLOAD)
You must accept this competition’s rules before you’ll be able to download data files.
IMPORTANT NOTE: The information provided below is intended only to provide general guidance to participants in the Heritage Health Prize Competition and is subject to the Competition Official Rules. Any capitalized term not defined below is defined in the Competition Official Rules. Please consult the Competition Official Rules for complete details.
Heritage Provider Network is providing Competition Entrants with deidentified member data collected during a forty-eight month period that is allocated among three data sets (the “Data Sets”). Competition Entrants will use the Data Sets to develop and test their algorithms for accurately predicting the number of days that the members will spend in a hospital (inpatient or emergency room visit) during the 12-month period following the Data Set cut-off date.
HHP_release2.zip contains the latest files, so you can ignore HHP_release1.zip. SampleEntry.CSV shows you how an entry should look.
Data Sets will be released to Entrants after registration on the Website according to the following schedule:
April 4, 2011 Claims Table – Y1 and DaysInHospital Table – Y2
May 4, 2011
All other Data Sets except Labs Table and Rx Table
The $3 million Heritage Health Prize opens to entries
By now, people have had a good chance to poke around the first portion of the data. Now the fun starts! HPN have released two more years’-worth of data, set the accuracy threshold and are opening up the competition to entries. The data are available from the Heritage Health Prize page. Good luck to all participants!
The Deloitte/FIDE Chess Ratings Competition results
ICDAR 2011 Competition Results
Revolution R Enterprise
As many of you know, Kaggle offers a free platform, Kaggle-in-Class, for instructors who want to host competitions for their students. For those interested in hearing more about the use of Kaggle-in-Class as a teaching tool, Susan Holmes and Nelson Ray from Stanford University share their experience in a webinar organized by the Consortium for the Advancement of Undergraduate Statistics Education.
- Data Mining to change the world of health care (decisionstats.com)
Here is an interview with Anne Milley, a notable thought leader in the world of analytics. Anne is now Senior Director, Analytical Strategy in Product Marketing for JMP , the leading data visualization software from the SAS Institute.
Ajay-What do you think are the top 5 unique selling points of JMP compared to other statistical software in its category?
JMP combines incredible analytic depth and breadth with interactive data visualization, creating a unique environment optimized for discovery and data-driven innovation.
With an extensible framework using JSL (JMP Scripting Language), and integration with SAS, R, and Excel, JMP becomes your analytic hub.
JMP is accessible to all kinds of users. A novice analyst can dig into an interactive report delivered by a custom JMP application. An engineer looking at his own data can use built-in JMP capabilities to discover patterns, and a developer can write code to extend JMP for herself or others.
State-of-the-art DOE capabilities make it easy for anyone to design and analyze efficient experiments to determine which adjustments will yield the greatest gains in quality or process improvement – before costly changes are made.
Not to mention, JMP products are exceptionally well designed and easy to use. See for yourself and check out the free trial at www.jmp.com.
Ajay- What are the challenges and opportunities of expanding JMP’s market share? Do you see JMP expanding its conferences globally to engage global audiences?
We realized solid global growth in 2010. The release of JMP Pro and JMP Clinical last year along with continuing enhancements to the rest of the JMP family of products (JMP and JMP Genomics) should position us well for another good year.
With the growing interest in analytics as a means to sustained value creation, we have the opportunity to help people along their analytic journey – to get started, take the next step, or adopt new paradigms speeding their time to value. The challenge is doing that as fast as we would like.
We are hiring internationally to offer even more events, training and academic programs globally.
Ajay- What are the current and proposed educational and global academic initiatives of JMP? How can we see more JMP in universities across the world (say India- China etc)?
We view colleges and universities both as critical incubators of future JMP users and as places where attitudes about data analysis and statistics are formed. We believe that a positive experience in learning statistics makes a person more likely to eventually want and need a product like JMP.
For most students – and particularly for those in applied disciplines of business, engineering and the sciences – the ability to make a statistics course relevant to their primary area of study fosters a positive experience. Fortunately, there is a trend in statistical education toward a more applied, data-driven approach, and JMP provides a very natural environment for both students and researchers.
Its user-friendly navigation, emphasis on data visualization and easy access to the analytics behind the graphics make JMP a compelling alternative to some of our more traditional competitors.
We’ve seen strong growth in the education markets in the last few years, and JMP is now used in nearly half of the top 200 universities in the US.
Internationally, we are at an earlier stage of market development, but we are currently working with both JMP and SAS country offices and their local academic programs to promote JMP. For example, we are working with members of the JMP China office and faculty at several universities in China to support the use of JMP in the development of a master’s curriculum in Applied Statistics there, touched on in this AMSTAT News article.
Ajay- What future trends do you see for 2011 in this market (say top 5)?
Growing complexity of data (text, image, audio…) drives the need for more and better visualization and analysis capabilities to make sense of it all.
More “chief analytics officers” are making better use of analytic talent – people are the most important ingredient for success!
JMP has been on the vanguard of 64-bit development, and users are now catching up with us as 64-bit machines become more common.
Users should demand easy-to-use, exploratory and predictive modeling tools as well as robust tools to experiment and learn to help them make the best decisions on an ongoing basis.
All these factors and more fuel the need for the integration of flexible, extensible tools with popular analytic platforms.
Ajay-You enjoy organic gardening as a hobby. How do you think hobbies and unwind time help people be better professionals?
I am lucky to work with so many people who view their work as a hobby. They have other interests too, though, some of which are work-related (statistics is relevant everywhere!). Organic gardening helps me put things in perspective and be present in the moment. More than work defines who you are. You can be passionate about your work as well as passionate about other things. I think it’s important to spend some leisure time in ways that bring you joy and contribute to your overall wellbeing and outlook.
Btw, nice interviews over the past several months—I hadn’t kept up, but will check it out more often!
Biography- Source- http://www.sas.com/knowledge-exchange/business-analytics/biographies.html
Anne Milley is Senior Director of Analytics Strategy at JMP Product Marketing at SAS. Her ties to SAS began with bank failure prediction at Federal Home Loan Bank Dallas and continued at 7-Eleven Inc. She has authored papers and served on committees for F2006, KDD, SIAM, A2010 and several years of SAS’ annual data mining conference. Milley is a contributing faculty member for the International Institute of Analytics. email@example.com
message from the official google blog-
With programs like Computer Science for High School (CS4HS), we hope to increase the number of CS majors —and therefore the number of people entering into careers in CS—by promoting computer science curriculum at the high school level.
For the fourth consecutive year, we’re funding CS4HS to invest in the next generation of computer scientists and engineers. CS4HS is a workshop for high school and middle school computer science teachers that introduces new and emerging concepts in computing and provides tips, tools and guidance on how to teach them. The ultimate goals are to “train the trainer,” develop a thriving community of high school CS teachers and spread the word about the awe and beauty of computing.
If you’re a university, community college, or technical School in the U.S., Canada, Europe, Middle East or Africa and are interested in hosting a workshop at your institution, please visit www.cs4hs.com to submit an application for grant funding.Applications will be accepted between January 18, 2011 and February 18, 2011.
In addition to submitting your application, on the CS4HS website you’ll find info on how to organize a workshop, as well as websites and agendas from last year’s participants to give you an idea of how the workshops were structured in the past. There’s also a collection ofCS4HS curriculum modules that previous participating schools have shared for future organizers to use in their own program.
- Supporting computer science education with CS4HS (googleblog.blogspot.com)
- Tell the US Federal Government how to fix K-12 CS Ed (computinged.wordpress.com)
- Google Reflects on Its Contributions to Computer Science Education (searchenginejournal.com)
- A Joint Call for Research on Why Computer Science Education is Important for K-12 (computinged.wordpress.com)
- Do High Schools Know What ‘Computer Science’ Is? (developers.slashdot.org)
- Advice On Teaching Linux To CS Freshmen? (ask.slashdot.org)
- Celebrating the second Computer Science Education Week (googleblog.blogspot.com)