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Maiia Bakhova
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  • San Diego
  • United States
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Profile Information

Job Title:
Data Scientist
Short Bio:
Mathematics PhD seeking a Data Scientist position at a progressive tech company. I have diverse data-manipulation experience critical to answering thoughtful scientific and marketplace questions. I apply a thorough and creative perspective to problem solving, and readily develop new skills to address yet unanswered problems. I am proficient in multiple computer languages, have experience presenting and teaching to diverse audiences, and am passionate about big data technologies.
Here is my data science blog:
LinkedIn Profile:
Finding a new position, Networking

San Diego Water Pollution Map

I have been working with San Diego Water quality dataproject:

Here are data sets:

Regretfully my complete works do not fit into the blog post (or even a few posts) because of a post size restriction (1 Mb). Here is a repository for it:

In particular I created a number of maps. You can see below one of them, where sizes of station marks correlate to pollution amounts:

Maiia Bakhova's Blog

Online Ad selection: Upper Confidence Bound method and Thompson Sampling method

Posted on February 28, 2019 at 10:00am 0 Comments

The post is devoted to select the most popular ad to display on a webpage to gather the most clicks. The rate at which the webpage visitors click on an ad is called a conversion rate for the add.

Assume that we have several ads and a place on a webpage to show one of them. We can display them one by one, record all the clicks, analyse the results afterwards and figure the most popular. But an ad display may be pricey. It would be more efficient to estimate rates in real time and to…


San Diego Water Pollution Map by Stations

Posted on November 6, 2018 at 11:46am 0 Comments

I have been working with San Diego Water quality data project:

Here are data sets:

Regretfully my complete works do not fit into the blog post (or even a few posts) because of a post…


Neural Networks as a Corporation Chain of Command

Posted on June 26, 2017 at 10:00am 2 Comments

Neural networks are considered complicated and they are always explained using neurons and a brain function. But we do not need to learn how to brain works to understand Neural networks structure and how they operate. We can look as something people encounter in everyday life more often, like a corporation hierarchy.…


Detection of Practical Dependency of Variables with Confidence Intervals

Posted on November 2, 2016 at 11:30am 0 Comments

This is an article which attempts to detect dependable variables with non-linear method.

I'm going to apply a method for checking variable dependency which was introduced in my previous post. Because the "dependency" I get with this rule is not true dependency as defined in Probability then I will call variables practically dependent at a confidence level…


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At 6:06am on February 22, 2016, Scott Sobel said…

Sure, I will do that. Thank you for your insights...



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