According to Google Trends, interest in the term 'machine learning' (ML) has increased over 300% since 2013. The world has watched ML go from the realm of a relatively small number of data scientists to the mainstream of analysis and business. And while this has resulted in a plethora of innovations and improvements among our customers and for organisations worldwide, it's also provoked reactions ranging from curiosity to anxiety among people everywhere.Source: IB Times
Crunchbase lists over 5,000 startups who are relying on machine learning for their main and ancillary applications, products and services today.Source: HOB
The analytics and business intelligence marketplace are crowded as ever. The scope of what constitutes analytics package could be a bit muzzy, and this makes choosing the simplest doable metal tool a frightening task. Modern tools cover way more than heritage reportage, with capabilities starting from information integration and information preparation to information quality, governance, and even machine learning.Source: HOB
The tools used for data science are rapidly changing at the moment, according to Gartner, which said we're in the midst of a "big bang" in its latest report on data science and machine learning platforms.Source: HOB
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