(EMAILWIRE.COM, September 04, 2018 ) The global machine learning market is estimated to grow at a CAGR of 49.7% during the forecast period 2017 – 2025 and accounts for US$ 39.98 Bn in the year 2025.

Machine learning is a branch of artificial intelligence that enables machine to develop the ability for self-learning and adaption through experience without being explicitly programmed. It is considered as a method of data analysis that automates analytical model building. Machine learning have been present from decades but not been widely used due to lack of big data it requires for processing. Over the last several decades, enterprises have depend greatly on analytics to provide them with competitive advantage and enable them to be more effective. But, enterprises now wants real time analytics and the capability to transform data into actionable insight. With the universality of data and the apparently vast scalability of cloud-based compute power, machine learning has become a huge trend across industries from last two years. Most of the pilot projects have been conducted in the year 2015 and the industry has started the adopting the real machine learning application in year 2016.

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The machine learning market segmentation is done on the basis of solution, deployment type and end-user. Furthermore, the end-users segment have been subdivided on the basis of machine learning applications for each end-user. The solution segment of machine learning market is bifurcated into software and services. The deployment type for machine learning is also bifurcated into cloud or machine learning as a service (MLaaS) market and on-premise machine learning market. The end-users segment for machine learning market include BFSI, retail, government, healthcare, manufacturing and others. For each of the end-user sector, machine learning has unique and different subset of applications. Fraud & Risk Management, Predictive Customer Analytics, Algorithm Trading, and Others are the applications covered under the BFSI sector. Customer Experience & Insight, Supply & Demand Planning, and Others applications are used for machine learning in the retail sector. Under the Healthcare sector, the machine learning applications include Diagnosis and Treatment Systems, Image Analytics & Diagnosis, and Others. Also, for the manufacturing sector, the machine learning applications have been bifurcated into Predictive Maintenance and Supply Chain Management. The applications of machine learning for Government sector have been segmented into Fraud & Improper Payments and Public Safety & Security. On the basis of geography, the Machine Learning market is analyzed into North America, Europe, Asia- Pacific (APAC), Middle East & Africa (MEA) and South America (SAM).

Ease of deployment and pay per usage are the major drivers towards the high growth of cloud/MLaaS across all regions. Large enterprises has to process a large amount of data using cloud computing and hence cloud/MLaaS are considered as the most preferred mode of deployment of machine learning services. Cloud/MLaaS offers the enterprise with a wide range of machine learning services with cost effective and easy deployment manner. It provides the enterprise an easy access to various specialized tools such as customer analytics, chatbots, and public safety & security are among others. Cloud based MSS provides the businesses with the shifting of IT expenses to operating expenditure rather than capital expenditure and provides an opportunity to leverage advanced machine learning capabilities.

Some of the global key players operating in the machine learning market are Google, Inc., Amazon Web Services, Inc., SAS Institute Inc., IBM Corporation and Microsoft Corporation. Also, Fair Isaac Corporation, Hewlett Packard Enterprise, SAP SE, BigML, Inc., and H2O.ai are other key companies in the machine learning market.

Highlights key business priorities in order to assist companies to realign their business strategies.
- The key findings and recommendations highlight crucial progressive industry trends in the machine learning market, thereby allowing players to develop effective long term strategies.
- Develop/modify business expansion plans by using substantial growth offering developed and emerging markets.
- Scrutinize in-depth global market trends and outlook coupled with the factors driving the market, as well as those hindering it.
- Enhance the decision-making process by understanding the strategies that underpin commercial interest with respect to products, segmentation and industry verticals.

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