Crunchbase lists over 5,000 startups who are relying on machine learning for their main and ancillary applications, products and services today.
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As 2018 comes to a close, it's worth taking some time to look back on the major events that occurred this year in the big data, data science, and AI space. Data security continued to be a major topic in 2018, particularly as the rash of big data breaches continued.
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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: HOB6429
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.
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Data is run by Deep learning algorithms through multiple layers of the algorithms of the neural network each of which passes a simplified representation of the data to the next layer.
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There are 8,705 startups and companies listed in Crunchbase today who are relying on machine learning for their main and ancillary applications, products, and services.
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Data Science Tools, Data Analysis, Data Warehousing, Data Mining, Microsoft Azure, MySQL, DataRobot, Amazon
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DataRobot wants to make machine learning so simple that a business analyst with basic training can run predictive models without breaking a sweat.
Source: HOB4119
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