aflyax github.io

data dendrites

exploring data science with Python et al.

OVERVIEW

The site aflyax.github.io presently has a traffic classification of zero (the lower the more traffic). We have crawled nine pages within the web page aflyax.github.io and found two websites referencing aflyax.github.io. We have unearthed two public web sites acquired by aflyax.github.io.
Pages Parsed
9
Links to this site
2
Social Links
2

AFLYAX.GITHUB.IO TRAFFIC

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

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LINKS TO AFLYAX.GITHUB.IO

Matthew Kirk

In Only 30 Minutes, You Can. Start A Machine Learning Project. I want to start my project! Because You Just Want to Start Coding.

Alfredo Motta Software Engineering, Machine Learning and Innovation blog.

Software Engineering, Machine Learning and Innovation blog. Get help from me on Codementor. Data manipulation primitives in R and Python. Why I loved the 2015 Railsconf Keynote. Upload video files with progress bar using Rails, Paperclip and Javascript. Cross validation is an essential tool in statistical learning.

WHAT DOES AFLYAX.GITHUB.IO LOOK LIKE?

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

AFLYAX.GITHUB.IO SERVER

We found that the main root page on aflyax.github.io took one hundred and seventy-two 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
0.172 sec
SSL
NOT SECURE
IP
151.101.40.133

SERVER SOFTWARE

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

SITE TITLE

data dendrites

DESCRIPTION

exploring data science with Python et al.

PARSED CONTENT

The site had the following in the web page, "Exploring data science with Python et al." I observed that the web site stated " I have recently participated in Kaggles Otto Challenge." They also stated " And got in the top 10 on the leaderboard. It was a fairly standard classification challenge, where a class of a product was predicted based on 93 numerical features. I will gradually write a couple posts about the methods I used, but here is a brief summary."

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