This article was posted on Mashape by Chris Ismael. Chris is a developer evangelist with proven success and experience in technical evangelism, business development, and software development in the mobile industry. Wikipedia defines Machine Learning as "a branch of artificial intelligence that deals with the construction and study of systems that can learn from data." Below is a compilation of APIs that have benefited from Machine Learning in one way or another, we truly are living in the future so strap into your rocketship and prepare for blastoff. Face and Scene recognition provided by ReKognition.com
This blog about machine learning was written by Emily Barry. Emily is a Data Scientist in San Francisco, California. Another thing she loves is data science. The more she learns about machine learning algorithms, the more challenging it is to keep these subjects organized in her brain to recall at a later time. So, she decided to marry these two loves in as productive a fashion as possible.
These articles were controversial in the sense that they highlighted the differences between data science and other disciplines, at a time when many believed that data science was just old stuff being re-branded, or being practiced by people knowing nothing about statistics. Analytics practitioners and users grew by a factor 5 over the last three years, faster than they can be properly trained, despite the numerous programs available for free, including ours (for self-learners only). Thus many are not equipped with the proper training. This created an opportunity to develop efficient, simple methods that could be understood and properly used by the layman, and even by robots, to process modern, big data. Unfortunately, this aspect of data science is considered by many, even today, to not be part of the core data science framework: it has created much of the controversy, mostly around the concept of automated data science, automated machine learning, or automated statistical science, including the introduction of new powerful algorithms such as automated indexation - a very fast clustering algorithm for big, unstructured text data - to create large taxonomies, by companies such as Amazon or Google.
A Data Scientist, according to Harvard Business Review, "is a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data". Therefore it comes as no surprise that Data Scientists are coveted professionals in the Big Data Analytics and IT industry. A report by Glassdoor shows that Data scientists lead the pack for the best jobs in America. The report goes on to say that the median salary for a Data Scientist is an impressive $116,000 and there are over 1,736 job openings posted on the site (Source). A Data Scientist dons many hats in his/her workplace.