Global Machine Learning as a Service Market: Overview
This report on the global machine learning as a service market provides analysis for the period 2015–2025, wherein 2016 is the base year and the period from 2017 to 2025 is the forecast period. Data for 2015 has been included as historical information. The report covers market dynamics including drivers, restraints opportunities, and trends expected to influence the global machine learning as a service market growth during the said period.
Technologies that are playing a major role in the driving the global machine learning as a service market have also been covered in the study. The study provides a comprehensive analysis on market growth throughout the above forecast period in terms of revenue estimates (in US$ Mn), across different geographies.
Global Machine Learning as a Service Market: Segmentation
The machine learning as a service market has been segmented on the basis of deployment type and end use application. Based on deployment type, the market has been further classified into public cloud and private cloud. By end use application, the market is further classified into manufacturing, retail, healthcare & life sciences, telecom, BFSI and others (energy & utilities, education, government etc.)
Geographically, the report classifies the global machine learning as a service market into North America, Europe, Asia Pacific, Middle East & Africa (MEA), and South America; the regions are analyzed in terms of revenue generation. Furthermore, region wise prominent countries covered in the report include the following - the U.S, Canada, Germany, France, the U.K., China, India, Japan, Australia, UAE, Saudi Arabia, South Africa, Brazil and Argentina.
Global Machine Learning as a Service Market: Scope of the Study
The report further includes key developments in the machine learning as a service market form 2006 onwards. Porter Five Force analysis which identifies bargaining power of supplier, bargaining power of buyer, threat from new entrant, threat from substitute and threat from competition in machine learning as a service market is also included in the report. Ecosystem analysis which identifies key stake holders in the machine learning as a service market is also covered in the report.
The report also covers segment wise comparison matrix, market attractiveness analysis and market share analysis for all regions covered in the scope of study.
Comparison matrix includes segment growth matrix, 2017 - 2025 (%), segment revenue contribution, 2017 - 2025 (%), and segment compounded growth matrix (CAGR %). Market attractiveness identifies and compares segments market attractiveness on the basis of CAGR and market share index.
Global Machine Learning as a Service Market: Competitive Landscape
In conclusion, the report presents the competition landscape which include competition matrix, market share analysis of major players in the global machine learning as a service market based on their 2016 revenues and profiles of major players. Competition matrix benchmarks leading players on the basis of their capabilities and potential to grow. Factors including market position, offerings and R&D focus are attributed to company’s capabilities. Factors including top line growth, market share, segment growth, infrastructure facilities and future outlook are attributed to company’s potential to grow. This section also identifies and includes various recent developments carried out by the leading players.
Company profiling includes company overview, major business strategies adopted, SWOT analysis and market revenues for year 2014 to 2016. The key players profiled in the global machine learning as a service market include IBM Corporation, Google Inc., Amazon Web Services, Microsoft Corporation, BigMl Inc., FICO, Yottamine Analytics, Ersatz Labs Inc, Predictron Labs Ltd and H2O.ai. Other players include ForecastThis Inc., Hewlett Packard Enterprise, Datoin, Fuzzy.ai, and Sift Science Inc. among others.
The global machine learning as a service market is segmented as below:
By Deployment Type
By End-use Application