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A complete visual guide on how Machine Learning works, different methods & its evolution

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We are entering a phase of massive digital transformation powered by the use of AI systems & Machine Learning algorithms. These technology enablers are seeing an exponential growth in enterprise level solutions. According to some estimates AI systems will top $46 billion by 2020. The only hindrance in the adoption of this revolutionary technology has been the skills gap & the lack of familiarity, but with the increased spending on R&D and continued training should address this problem sooner than later. For connected consumers Machine Learning presents an interesting opportunity to enable on demand services.

A good example in this regard is an AI driven platform Rise which has outperformed the Stock market performance consistently based on its Machine Learning algorithms and is now looking to enter the Crypto markets. Needless to stay automation is gathering pace across all sectors of the global ecosystem. Machine Learning has evolved greatly since its inception from a simple example of separating emails based on a filter, to more complex tasks like mapping sites in real-time and assessing the reconstruction costs etc. quickly & accurately. The following infographics will give you a comprehensive understanding of Machine Learning’s different methods, how they are used & how it has evolved over the years.

Machine Learning cyberregression

classification

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Faisal Khan
Faisal is based in Canada with a background in Finance/Economics & Computers. He has been actively trading FOREX for the past 11 years. Faisal is also an active Stocks trader with a passion for everything Crypto. His enthusiasm & interest in learning new technologies has turned him into an avid Crypto/Blockchain & Fintech enthusiast. Currently working for a Mobile platform called Tradelike as the Senior Technical Analyst. His interest for writing has stayed with him all his life ever since started the first Internet magazine of Pakistan in 1998. He blogs regularly on Financial markets, trading strategies & Cryptocurrencies. Loves to travel.

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