DUBLIN--(BUSINESS WIRE)--The "Global Machine Learning as a Service Market Size, Share & Industry Trends Analysis Report By End User, By Offering, By Organization Size, By Application, By Regional Outlook and Forecast, 2022 - 2028" report has been added to ResearchAndMarkets.com's offering.
The Global Machine learning as a Service Market size is expected to reach $36.2 billion by 2028, rising at a market growth of 31.6% CAGR during the forecast period.
Machine learning is a data analysis method that includes statistical data analysis to create desired prediction output without the use of explicit programming. It uses a sequence of algorithms to comprehend the link between datasets in order to produce the desired result. It is designed to include artificial intelligence (AI) and cognitive computing functionalities. Machine learning as a service (MLaaS) refers to a group of cloud computing services that provide machine learning technologies.
Increased demand for cloud computing, as well as growth connected with artificial intelligence and cognitive computing, are major machine learning as service industry growth drivers. Growth in demand for cloud-based solutions, such as cloud computing, rise in adoption of analytical solutions, growth of the artificial intelligence & cognitive computing market, increased application areas, and a scarcity of trained professionals are all influencing the machine learning as a service market.
As more businesses migrate their data from on-premise storage to cloud storage, the necessity for efficient data organization grows. Since MLaaS platforms are essentially cloud providers, they enable solutions to appropriately manage data for machine learning experiments and data pipelines, making it easier for data engineers to access and process the data.
For organizations, MLaaS providers offer capabilities like data visualization and predictive analytics. They also provide APIs for sentiment analysis, facial recognition, creditworthiness evaluations, corporate intelligence, and healthcare, among other things. The actual computations of these processes are abstracted by MLaaS providers, so data scientists don't have to worry about them. For machine learning experimentation and model construction, some MLaaS providers even feature a drag-and-drop interface.
Market Growth Factors
Increased Demand for Cloud Computing and a Boom in Big Data
The industry is growing due to the increased acceptance of cloud computing technologies and the use of social media platforms. Cloud computing is now widely used by all companies that supply enterprise storage solutions. Data analysis is performed online using cloud storage, giving the advantage of evaluating real-time data collected on the cloud.
Cloud computing enables data analysis from any location and at any time. Moreover, using the cloud to deploy machine learning allows businesses to get useful data, such as consumer behavior and purchasing trends, virtually from linked data warehouses, lowering infrastructure and storage costs. As a result, the machine learning as a service business is growing as cloud computing technology becomes more widely adopted.
Use of Machine Learning to Fuel Artificial Intelligence Systems
Machine learning is used to fuel reasoning, learning, and self-correction in artificial intelligence (AI) systems. Expert systems, speech recognition, and machine vision are examples of AI applications. The rise in the popularity of AI is due to current efforts such as big data infrastructure and cloud computing.
Top companies across industries, including Google, Microsoft, and Amazon (Software & IT); Bloomberg, American Express (Financial Services); and Tesla and Ford (Automotive), have identified AI and cognitive computing as a key strategic driver and have begun investing in machine learning to develop more advanced systems. These top firms have also provided financial support to young start-ups in order to produce new creative technology.
Market Restraining Factors
Technical Restraints and Inaccuracies of ML
The ML platform provides a plethora of advantages that aid in market expansion. However, several parameters on the platform are projected to impede market expansion. The presence of inaccuracy in these algorithms, which are sometimes immature and underdeveloped, is one of the market's primary constraining factors.
In the big data and machine learning manufacturing industries, precision is crucial. A minor flaw in the algorithm could result in incorrect items being produced. This is expected to exorbitantly increase the operational costs for the owner of the manufacturing unit than decrease it.
Scope of the Study
Market Segments Covered in the Report:
By End User
- IT & Telecom
- BFSI
- Manufacturing
- Retail
- Healthcare
- Energy & Utilities
- Public Sector
- Aerospace & Defense
- Others
By Offering
- Services Only
- Solution (Software Tools)
By Organization Size
- Large Enterprises
- Small & Medium Enterprises
By Application
- Marketing & Advertising
- Fraud Detection & Risk Management
- Computer vision
- Security & Surveillance
- Predictive analytics
- Natural Language Processing
- Augmented & Virtual Reality
- Others
By Geography
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Key Market Players
- Hewlett-Packard Enterprise Company
- Oracle Corporation
- Google LLC
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- IBM Corporation
- Microsoft Corporation
- Fair Isaac Corporation (FICO)
- SAS Institute, Inc.
- Yottamine Analytics, LLC
- BigML
For more information about this report visit https://www.researchandmarkets.com/r/ujjbul
