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Profile Information

Short Bio:
Algolytics is software development company offering tools for Predictive Analytics, Data Quality, Social Network Analysis and other advanced data analysis tasks.

Read more:
Job Title:
Predictive Analytics | Data Quality | Machine Learning | Stream Based Modeling
C-Level/SVP/Executive Team
Job Function:
Number of employees:
1 to 49
LinkedIn Profile:
Networking, New venture
Topics of Interest
Data Science, Machine Learning, Deep Learning, Enterprise Data Modeling, Fintech, Internet of Things (IoT), Business Analytics, Data Strategy, Artificial General Intelligence

Algolytics's Blog

Approximation or Classification – which one to choose?

Posted on June 2, 2021 at 1:00am 0 Comments

Among the many decisions you’ll have to make when building a predictive model is whether your business problem is either a classification or an approximation task. It’s an important decision because it determines which group of methods you choose to create a model: classification (decision trees, Naive Bayes) or approximation (regression tree,…


Understanding Machine Learning: How machines learn?

Posted on April 13, 2017 at 4:00am 3 Comments

“If (there) was one thing all people took for granted, (it) was conviction that if you feed honest figures into a computer, honest figures (will) come out. Never doubted it myself till I met a computer with a sense of humor.”

― Robert A. Heinlein, The Moon is a Harsh Mistress


This post is the first in a series of articles in which we will explain what Machine Learning is. You don’t have to have formal training or…


Correlation does not imply causation

Posted on December 13, 2016 at 4:30am 1 Comment

A popular phrase tossed around when we talk about statistical data is “there is correlation between variables”. However, many people wrongly consider this to be the equivalent of “there is causation between variables”. It’s important to explain the distinction: Correlation means that once we know how one variable changes we can make reasonable deductions about how other variables change There are several variants of correlation:

1. Positive…


Understanding machine learning #3: Confusion matrix - not all errors are equal

Posted on November 13, 2016 at 4:30am 0 Comments

One of the most typical tasks in machine learning is classification tasks. It may seem that evaluating the effectiveness of such a model is easy. Let’s assume that we have a model which, based on historical data, calculates if a client will pay back credit obligations. We evaluate 100 bank customers and our model correctly guesses in 93 instances. That may appear to be  a good result – but is it really? Should we consider a model with 93% accuracy as adequate?

It depends. Today, we…


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