# Math for Data Science — Vol 2

## Statistics and Probability.

Math can be compared to octopus. It has several tentacles that can touch practically every aspect of our life. Some subjects receive only a slight touch, and others are wrapped like a clam in the tentacles’ vice-like grip. Data science is one of the second kinds.

There are lots of connections between math and data science, and vice versa, but statistics at the heart of this construction. A lot of statistical models, for example, logistic or linear regression — are already methods for machine learning by themselves, so in some way, these two fields are intertwined into one entity.

Evaluation…

# Math for Data Science — Vol 1

## Functions, Multivariable Calculus & Graphs.

Math is quite daunting, especially for folks coming from a non-technical background. There are plenty of things you can easily get confused with and then lose motivation. But despite its complexity, math is an integral condition to manipulate data effectively. Ignoring it is the worst sin you can ever do.

How to overcome the fear of math?

First off, you shouldn’t be a math geek or finish a Ph.D. in let say linear algebra. Projects in Data Science may vary and may deal with phenomena as diverse as a cancer diagnosis or social behavior analysis, etc.

Secondly, there is no…

# Facial recognition: 8 Open-source tools to detect faces

## Facial recognition tools for everyone… but how? Let’s see.

Facial recognition is everywhere making complex tasks simpler. Automated login to your phone, more convenient access to biometric data, fast identification at security gates, making purchases like pay for your chicken, or even finding your dream couple. Today we can use facial recognition in all possible cases.

As a rule, huge companies have separate teams of engineers to implement this technology. But what if you are an alone soldier, or you have no or little engineering background? Hopefully, there are a variety of open-source tools that allow seeing the power of facial recognition in practice for everyone.

Using these tools…

# Learn Data Science in 2021: Books, Blogs, YouTube channels & More

## A comprehensive selection of sources.

You heard it before: we are what information we consume. That’s why when it comes to acquiring new knowledge or just following the latest trends, it is essential to be selective with the choice of sources to get information.

As a curious person and practitioner in the field of AI, ML, and Data Science, I never stop my research, and I see myriads of blogs everyday. So, I decided to gather the most insightful and valuable stuff (as I see it) in one place to help others in their growth.

You will not find mainstream stuff here or something everyone…

# I’m back on Medium. What happened with AI during 2020 up to now?

## Breakthroughs that shaped AI in 2020.

Hello, reader. I am Oleksii, and I have been involved in the world of AI and Data Science for over 4 years. I am just an entrepreneur with many ideas and a big desire to spread knowledge and make things simpler.

A long time ago in a galaxy far, far away… I was already here, leading my blog on Medium, where I covered all of my insights and thoughts on AI, ML, Data Science. But one day, I discovered my blog disappeared from the surface of Medium, and mainly Towards Data Science, where all of my articles appeared very often.

## Oleksii Kharkovyna

Bits and pieces on AI, Machine Learning & Data Science

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