Pune, Maharashtra -- (SBWIRE) -- 06/19/2020 -- Manhattan, New York, Analytical Research Cognizance: The Machine Learning Infrastructure as a Service market is projected to witness momentous growth over the upcoming years due to a tremendous rise in demand due to the global COVID-19 pandemic. The report includes an in-depth, extensive study of this market in tandem with vital parameters that are likely to have an effect on the market commercialization matrix.
Machine learning infrastructure as a service market was valued at nearly USD 900 million in 2019, growing with a CAGR surpassing 40% in the forecast period. Machine learning is a computational technology that provides computers with the ability to learn and adjust their analytical functions without being specifically programmed when exposed to new data sets. The growth of machine learning along with its related advanced market in computing and analytics is caused by several factors. Some of them are growing consumer mapping demand, especially by the marketing and advertising industry, increased security concerns and a growing need for support applications in an emergency. In enabling technologies, rapid progress and innovations are taking place. In such areas, a variety of solution providers do a lot of work. For example, Affectiva recently started its emotional analytics technology which has over 2 million face video data repositories, which enables its customers to achieve high accuracy and unprecedented insights. In the field of gesture recognition, cognitive computers and neural research, face recognition, other industry participants such as the Cognitec Method, Emotient, Gesturetek, Saffron, and Palantir are also making significant advancements. This trend is expected to drive market growth in the years to come.
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Most organizations have little experience in managing infrastructure effectively and instead offer the services to third party suppliers in order to sustain the network and security standards. Professional services include the designing, planning, advisory and consulting services. The growth of professional services is primarily driven by the complexity of operations and the growing use of machine learning solutions in manufacturing. Professional services, including deployment & integration, support and maintenance, and advisory services are categorized into three types such as deployment & integration, support & maintenance, and consulting services. Machine learning is now being described as a pivotal tool for analytics sector, network and automated traffic management. This is primarily due to its exceptional growth of data across each vertical. Every day, large amounts of data traverse network infrastructure. With the advent of big data analytics and predictive analytics, this sector is anticipated to witness maximum growth since it can lead to accurate market predictions in short span of time. North America is leading the global market and will continue to grow at the highest rate. Presence of large IT hub and ITES offices in this region would definitely jolt the machine learning infrastructure as service market. Furthermore, countries such as U.S. and Canada have been extremely adoptive of the latest technological advancements including integration technologies with cloud, Big Data within Machine Learning Services.
Global machine learning infrastructure as a service market is segmented on the basis of Product, application and geography. Based on the Product, the global market is categorized into software tools, data storage, cloud and web-based application, others. On the basis of services, the global machine learning infrastructure as a service Market is bifurcated into professional, managed and others. On the basis of enterprises, the market is categorized into large enterprises and SMEs. Geographically, the market is divided into Asia-Pacific, North America, Europe, Latin America and (MEA).
Some of the key players operating within the global Machine Learning Infrastructure as a Service market include Microsoft, Google, Inc., BigML Inc., FICO, IBM Corporation, Hewlett Packard Enterprises, AT&T, Fuzzy.ai, Yottamine Analytics and Amazon Web Services.
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Some Points of TOC:
Chapter One: Market Introduction
Chapter Two: Executive Summary
Chapter Three: Global Machine Learning Infrastructure as a Service Market – Key Industry Dynamics
Chapter Four: Global Machine Learning Infrastructure as a Service Market – Analysis and Revenue Forecast, 2015-2025 – By Product Type
Chapter Five: Global Machine Learning Infrastructure as a Service Market – Analysis and Revenue Forecast, 2015-2025 – By Application
Chapter Six: Global Machine Learning Infrastructure as a Service Market – Analysis and Revenue Forecast, 2015-2025 – By End-Use
Chapter Seven: Global Machine Learning Infrastructure as a Service Market – Analysis and Revenue Forecast, 2015-2025 – By Region
Chapter Eight: North America Machine Learning Infrastructure as a Service Market – Analysis and Revenue Forecast, 2015-2025
Chapter Nine: Europe Machine Learning Infrastructure as a Service Market – Analysis and Revenue Forecast, 2015-2025
Chapter Ten: Asia-Pacific Machine Learning Infrastructure as a Service Market – Analysis and Revenue Forecast, 2015-2025
Chapter Eleven: Latin America Machine Learning Infrastructure as a Service Market – Analysis and Revenue Forecast, 2015-2025
Chapter Twelve: Middle East & Africa Machine Learning Infrastructure as a Service Market – Analysis and Revenue Forecast, 2015-2025
Chapter Thirteen: Competitive Analysis
Chapter Fourteen: Appendix
Chapter Fifteen: Research Conclusions
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Note:
Our report does take into account the impact of coronavirus pandemic and dedicates qualitative as well as quantitative sections of information within the report that emphasizes the impact of COVID-19.As this pandemic is ongoing and leading to dynamic shifts in stocks and businesses worldwide, we take into account the current condition and forecast the market data taking into consideration the micro and macroeconomic factors that will be affected by the pandemic.