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Olexander Kolisnykov's Page

Profile Information

Short Bio
Olexander is a tech journalist and content strategist who focuses on covering machine learning applications in business.
My Web Site Or LinkedIn Profile
http://https://www.linkedin.com/in/borisbromm/
Professional Status
Manager
Your Company:
AltexSoft
Your Job Title:
Content Strategist
Interests:
Networking
What is your Favorite Data Mining or Analytical Website?
http://kdnuggets.com

Olexander Kolisnykov's Blog

Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI, IBM Watson

Posted on September 18, 2018 at 2:52am 0 Comments

planets

For most businesses, machine learning seems close to rocket science, appearing expensive and talent demanding. And, if you’re aiming at building another Netflix recommendation system, it really is. But the trend of making everything-as-a-service has affected this sophisticated sphere, too. You can jump-start an ML initiative without much investment, which would be the right move if you are new to data science and just want to grab the low hanging fruit.

One of ML's…

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Time Series Analysis and Forecasting: Novel Business Perspectives

Posted on February 14, 2018 at 1:58am 0 Comments

Time series forecasting is hardly a new problem in data science and statistics. The term is self-explanatory and has been on business analysts’ agenda for decades now: The very first practices of time series analysis and forecasting trace back to the early 1920s.

The underlying idea of time series forecasting is to look at historical data from the time perspective, define the patterns, and yield short or long-term predictions on how –  considering the captured patterns – target…

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Supervised Learning Use Cases: Low-Hanging Fruit in Data Science for Businesses

Posted on January 18, 2018 at 3:00am 1 Comment

In the past few years, machine learning (ML) has revolutionized the way we do business. A disruptive breakthrough that differentiates machine learning from other approaches to automation is a step away from the rules-based programming.  ML algorithms allowed engineers to leverage data without explicitly programming machines to follow specific paths of problem-solving. Instead, machines themselves arrive at the right answers based on the data they have. This capability made business…

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