Machine learning as-a-service refers to various types of services that offer machine learning abilities as a part of cloud-computing services. MLaaS assists its customers to gain advantage from machine learning without additional cost, risk, and time for creating an in-house internal machine learning team. MLaaS offers various advantages such as data pre-processing, model evaluation, model training, and predications. Many service providers offer API, predictive analytics, deep learning, data visualization, natural language processing, etc. The major advantage that MLaaS offers to businesses is that it enables them to get started quickly with machine learning without undergoing tedious software installation processes. Companies can enhance their product capabilities and offerings, enhance regular business operation efficiency, make interaction with consumers easier, and use AI prediction capabilities.
The global machine learning as a service (MLaaS) market was valued at US$ 5,228.3 Mn in 2021.
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Machine Learning as a Service Market Report Coverage
Report Coverage | Details | ||
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Base Year: | 2021 | Market Size in 2021: | US$ 5,228.3 Mn |
Historical Data for: | 2017 to 2020 | Forecast Period: | 2022 to 2030 |
Forecast Period 2022 to 2030 CAGR: | 38.8% | 2030 Value Projection: | US$ 98,532.9 Mn |
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Companies covered: |
H2O.ai, Google Inc., Predictron Labs Ltd, IBM Corporation, Ersatz Labs Inc., Microsoft Corporation, Yottamine Analytics, Amazon Web Services Inc., FICO, and BigML Inc |
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Global Machine Learning as a Service Market - Impact of Coronavirus (Covid-19) Pandemic:
The COVID-19 pandemic has positively affected the global machine learning as a service (MLaaS) market. Moreover, Machine learning as a Service is widely used in Cloud Computing Services as they have the capability of data transformations, visualizations, predictive analytics, and data modeling APIs. But, due to the pandemic, many organizations accelerated their migrations to public cloud solutions, since cloud service elasticity meets unexpected growth in service demand.
Therefore, the global machine learning as a service (MLaaS) market witnessed high growth during the pandemic.
North America held a dominant position in the global machine learning as a service (MLaaS) market in 2021
Statistics:
North America region dominated the global machine learning as a service (MLaaS) market in 2021, accounting for a 32.8% share in terms of value, followed by Europe, Asia Pacific, and Latin America, respectively
Figure 1: Global machine learning as a service (MLaaS) Market Share (%), By Region, 2021
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North America and Europe were the two leading markets in terms of revenue in 2021, and are expected to hold their dominant position over the forecast period. The market growth in these regions is attributed to the growing technological industry. For instance, machine learning as a service (MLaaS) is majorly used for Cloud Computing Services, etc. in the technology industry, which is expected to drive demand for machine learning as a service (MLaaS) over the forecast period. Moreover, increasing demand for machine-learning tools as part of Cloud Computing Services in the machine learning as a service (MLaaS) is expected to facilitate the growth of the machine learning as a service (MLaaS) market in North America.
Figure 2: Global machine learning as a service (MLaaS) Market (US$ Mn) Analysis and Forecast, 2022 - 2030
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The global machine learning as a service (MLaaS) market was valued at US$ 5,228.3 Mn in 2021 and is expected to reach US$ 98,532.9 Mn by 2030, growing at a CAGR of 38.8% between 2022 and 2030.
Major players operating in the global machine learning as a service (MLaaS) market are H2O.ai, Google Inc., Predictron Labs Ltd, IBM Corporation, Ersatz Labs Inc., Microsoft Corporation, Yottamine Analytics, Amazon Web Services Inc., FICO, and BigML Inc.
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About Author
Ankur Rai is a Research Consultant with over 5 years of experience in handling consulting and syndicated reports across diverse sectors. He manages consulting and market research projects centered on go-to-market strategy, opportunity analysis, competitive landscape, and market size estimation and forecasting. He also advises clients on identifying and targeting absolute opportunities to penetrate untapped markets.
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