shftan github.io

Sarah Tan

Sarah Tan, PhD student, Cornell Statistics. Working on machine learning problems.

OVERVIEW

The site shftan.github.io presently has a traffic classification of zero (the lower the more traffic). We have crawled one page within the web page shftan.github.io and found two websites referencing shftan.github.io. We have unearthed three public web sites acquired by shftan.github.io.
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3

SHFTAN.GITHUB.IO TRAFFIC

The site shftan.github.io is seeing variant levels of traffic for the duration of the year.
Traffic for shftan.github.io

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LINKS TO SHFTAN.GITHUB.IO

Department of Statistical Sciences DSS Cornell University Department of Statistical Science

Click here to register for the Cornell Day of Statistics. The conference will take place at the Statler Hotel in the J. Willard Marriott Executive Education Center. Registration for the Cornell Day of Statistics. Cornell Day of Statistics Dinner. Our department offers three programs at the undergraduate and graduate levels. Students can earn a BA in either Biometry or Statistics. The MPS offers students the opportunity to.

WHAT DOES SHFTAN.GITHUB.IO LOOK LIKE?

Desktop Screenshot of shftan.github.io Mobile Screenshot of shftan.github.io Tablet Screenshot of shftan.github.io

SHFTAN.GITHUB.IO SERVER

We found that the main root page on shftan.github.io took one thousand two hundred and nineteen milliseconds to come up. Our web crawlers could not observe a SSL certificate, so in conclusion our crawlers consider this site not secure.
Load time
1.219 sec
SSL
NOT SECURE
IP
151.101.40.133

SERVER SOFTWARE

We discovered that shftan.github.io is weilding the GitHub.com operating system.

SITE TITLE

Sarah Tan

DESCRIPTION

Sarah Tan, PhD student, Cornell Statistics. Working on machine learning problems.

PARSED CONTENT

The site had the following in the web page, "PhD student, Cornell Statistics." I observed that the web site stated " H t 3 9 5 AT cornell DOT edu." They also stated " I am a 4th year PhD student at Cornell Statistics. Broadly, I work on inference and interpretability of machine learning methods, in particular tree-based methods, and causal inference. I am advised by Giles . My work is supported by a Harmony Institute Research Fellowship. Previously, I studied at Berkeley. I spent summer 2015 at Xerox Research."

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