Machine Learning as a Service (MLaaS) Industry - Changing On-Premises Opportunities For 2017

The global Machine Learning as a Service (MLaaS) market is valued at USD XX.XX billion in 2016, and is expected to reach USD XX.XX billion by 2022. The market is projected to grow at a CAGR of XX% over the forecast period of 2017-2022.

Machine Learning is defined as the science of getting computer systems to learn without any predefined programming. Machine learning is a branch of Artificial Intelligence and is used in various fields to continuously analyze data and make real-time decisions with any human interference. It focusses on teaching computers to learn from the environment and generate new data. It uses multiple techniques to analyze and detect patterns. Machine Learning is now being employed for applications such as face recognition, predictive analysis, deep learning, etc. With increasing awareness of machine learning, many companies are deploying this technology to achieve better productivity. Due to the increasing demand for machine learning solutions, many industries are opting for Machine Learning as a Service. MLaaS offers feasible Machine Learning solutions to organisations without the need for in-house infrastructure.

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Increasing adoption of Internet of Things technology in many industries is driving the growth of this industry. With increasing deployment of IoT systems, the amount of data that needs to be handled has increased drastically, which is calling for faster and reliable data analysis solutions. Also, companies are increasingly focusing on understanding consumer behavior, to address each consumer efficiently. This is driving investments in MLaaS solutions. Furthermore, innovations in automation technologies and increasing adoption of cloud-based systems is boosting the growth. However, the need for highly-skilled personal to develop and deploy the systems and issues regarding data security are restraining the growth of this market.

The global MLaaS market can be segmented by application (advertising & marketing, predictive maintenance, automated network management, risk analytics and fraud detection and others), organization size (small enterprises, medium enterprises and large enterprises), vertical (IT, automotive, healthcare, aerospace and defense, government, retail, media and entertainment, BFSI, education and others) and by region (North America, Europe, Asia-Pacific, Latin America and the Middle East & Africa)

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The report also considers key trends that will impact the industry and profiles of leading suppliers of MLaaS services, which include Microsoft Corp., IBM corp., Amazon Web Services, Google Inc., BigML Inc., Hewlett Packard Inc., FICO, PurePredictive Inc., among others

North America is leading in this market with the largest share, followed by Europe. While, Asia-Pacific is expected to be the fastest-growing market during the forecast period. Increasing adoption of cloud technologies and investments from global companies provide good opportunities in the Middle East and Latin American regions.

This report describes a detailed study of Porter's five forces analysis of the market. All the five major factors in these markets have been quantified using the internal key parameters governing each of them. It also covers the market landscape of top players, which includes the key growth strategies, geographical footprint, and competition analysis.

Key Deliverables of the Study:

• Market Definition for Machine Learning as a Service, along with identification of key drivers and restraints for the market.
• Market analysis for the global Machine Learning as a Service market, with region-specific assessments and competition analysis on a global and regional scale.
• Identification of factors instrumental in changing the market scenario, rising prospective opportunities and identification of key companies which can influence the market on a global and regional scale.
• Extensively researched competitive landscape section with profiles of major companies along with their strategic initiatives and market share.
• Identification and analysis of the macro and micro factors that affect the Machine Learning as a Service market on both, global and regional scale.
• A comprehensive list of key market players along with the analysis of their current strategic interests and key financial information.

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