Practical Machine Learning kentran.net

Practical Machine Learning

Ken Tran on machine learning, data technology, and beyond

OVERVIEW

This site kentran.net currently has a traffic classification of zero (the lower the superior). We have probed nineteen pages within the domain kentran.net and found three websites referring to kentran.net. We were able to note one contacts and directions for kentran.net to help you contact them. This site kentran.net has been on the internet for eight hundred and two weeks, fourteen days, fourteen hours, and thirty-one minutes.

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Online Since

Feb 2009

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KENTRAN.NET HISTORY

This site kentran.net was started on on February 16, 2009. This web page was updated on February 17, 2014. This website will expire on the date of February 16, 2015. It is now eight hundred and two weeks, fourteen days, fourteen hours, and thirty-one minutes old.

REGISTERED

February

2009

UPDATED

February

2014

EXPIRED

February

2015

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LINKS TO WEB PAGE

Microsoft Research - Turning ideas into reality - Microsoft Research

Machine Learning and Artificial Intelligence. More free apps and downloads . Using artificial intelligence for better answers. More about AI and weather forecasting .

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CONTACTS

KEN TRAN

KEN TRAN

4603 YELLOW ROSE TRL

AUSTIN, TX, 78749

1.5124711903

ONE@KENTRAN.NET

KENTRAN.NET HOST

We observed that the main root page on kentran.net took zero milliseconds to load. I could not discover a SSL certificate, so therefore our parsers consider this site not secure.

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0 seconds

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NOT SECURE

Internet Address

208.113.214.96

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PAGE TITLE

Practical Machine Learning

DESCRIPTION

Ken Tran on machine learning, data technology, and beyond

CONTENT

This site kentran.net states the following, "Friday, May 1, 2015." Our analyzers noticed that the webpage stated " Scaling Up Stochastic Dual Coordinate Ascent." The Website also stated " To appear at KDD 2015. There are two main ideas in this paper. A semi-asynchronous parallel SDCA algorithm that guarantees strong linear convergence and scales almost linearly with respect to the number of cores on large and sparse datasets. Cache efficiency is the key, as I mentioned in a previous blog post. Saturday, December 20, 2014. Is it really due to Neural Networks?."

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