Freelancing is in every field of journalism to technology. Though freelancing in the technology field is at an early stage, soon it will boom the market. To begin with, what is freelancing and how it is relevant to Data Scientist job? In simple terms, a freelancer is a person who can contribute to a company without being a part of it.

I have written this article to bring the focus on freelancing in Data Science as well as the importance of Data Science Foundation for it's facilitation for the Data Scientists......Request you all to share your valueable suggestions for this article....

The Big Data vs. AI compare and contrast it, in fact, a comparison of two very closely related data technologies. Is Big Data vs. artificial intelligence even a fair comparison? To some degree it is, but first let's cut through the confusion.

Request you all to please share your valuable suggestions, if there is any.Regards,Ajit Singh

A potentially useful intellectual tool for researchers is the ability to make connections between seemingly unrelated facts, and as a consequence create inspired new ideas, approaches or hypotheses for their current work. This can be achieved through a process known as text mining (or data mining if it focuses on non-bibliographic datasets).

Request you all to please provide your valuable suggestions......Regards,Ajit Singh

Intuitively, it seems that, with the advantage and insight that Data Science provides, Data Scientists should have been around for much longer, helping us make decisions? This question can be answered in one word. Data. Data is the bread and butter of a Data Scientist. A Data Scientist sleeps, breathes and eats data. Let's have a look at the lifestyle of a data scientist

A fun article on what the people who eat and breath data get up to on a day to day basis. Thanks for sharing

The programme for Advances in Data Science 2019 is now available. This year's meeting is themed around four topics: Health & Wellbeing, AI & Robotics, NLP & Text Mining and Security & Privacy. Invited speakers include leading data scientists from industry and academia.

Noted.....

Data Engineers are the data professionals who prepare the “big data” infrastructure to be analyzed by Data Scientists. They are software engineers who design, build, integrate data from various resources, and manage big data. They must have the certain key skills.

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A look at modern big data science systems and how you can use EXASOL's in-memory database for Data Science.

Informative EXASOL.....

HG Data, the global leader in technology intelligence and founder member of the Data Science Foundation has announced its new company name, HG Insights, ahead of this month’s Big Data World conference at ExCel London. The company’s Executive Vice President of Strategy, Tim Royston-Webb, will be giving a keynote presentation at this year’s event which will see the official launch of the new HG Insights Platform, with next generation technographics that boost business intelligence and ignite customer growth.

Informative......

This article in the Harvard Business Review is worth reading. It suggests that the drive to create efficient data science teams by employing specialists e.g. researchers, data engineers, machine learning experts, inference scientists etc. is the wrong approach. By narrowing the scope of the individual and creating efficiencies, you are removing the opportunity to learn and develop new capabilities.https://hbr.org/2019/03/why-data-science-teams-need-generalists-not-specialists

New Method of Data Regression Analysis

“New Square Method” Two-Dimensional Nonlinear data Regression Example