Dublin, Nov. 04, 2022 (GLOBE NEWSWIRE) — The “Global Machine Learning Market By Component, By Deployment, By Enterprise Size, By End User & By Region Forecast and Analysis 2022-2028” report has been added to ResearchAndMarkets.com’s offering.
Global machine learning market was valued at USD 16.2 billion in 2021, and it is expected to reach a value of USD 164.05 billion by 2028, at a CAGR of more than 39.2% over the forecast period (2022-2028).
Software programs may be able to accurately anticipate outcomes without being explicitly instructed to do so by making use of machine learning (ML), which is a type of artificial intelligence (AI).Algorithms for machine learning use past data as input to predict future output values. As businesses implement increasingly sophisticated security frameworks, machine learning will emerge as a significant security analytics trend, boosting the global machine learning market.
Because so much data is generated and sent across so many networks, cyber specialists have a difficult time identifying and analyzing potential cyber threats and attacks. Machine-learning algorithms can help businesses and security teams anticipate, detect, and recognize cyberattacks more quickly as cyber risks become more pervasive and sophisticated, with supply chain attacks increasing by 42% in the first quarter of 2021 in the United States, affecting up to 7,000,000 people.
This collaboration can help businesses from all industries, including the public sector, manufacturing, and financial services, innovate quickly and safely and address issues like ransomware, disruptions in supply chains, cyber threats, and the demand for frictionless services in the 5G era. During the forecast period, this is anticipated to boost the global machine learning market.
Segments covered in this report
Global machine learning market is segmented based on the component, enterprise size, deployment, end-user, and region. Based on the component, the global machine learning market is segmented into solutions, and services. Based on enterprise size, the market is segmented into SMEs and large enterprises.
Based on deployment, the global machine learning market is segmented into cloud and on-premise.
Based on end-users, the global machine learning market is segmented as healthcare, retail, IT and telecommunications, banking, financial services and insurance (BFSI), automotive & transportation, advertising & media, manufacturing, and others (energy & utilities, etc.). Based on region, it is categorized into North America, Europe, Asia-Pacific, Latin America, and MEA.
Numerous healthcare-related situations are already being improved by machine learning technology. The healthcare sector makes use of this technology, among other things, to precisely allocate resources, forecast outcomes, quickly assess risks, and evaluate millions of distinct data points.For instance, IBM Watson Health and Healthcare IT Leaders today made the announcement that a comprehensive set of corporate COVID-19 services, IBM Digital Health Pass and Healthcare IT Leaders Healthy Returns, would be combined.
Diagnostics with Medical Imaging: Combining machine learning and deep learning, computer vision is a cutting-edge technique. This has been approved by the Microsoft InnerEye initiative, which focuses on image diagnostic tools for image analysis. For instance, a group of IBM and Pfizer researchers created an artificial intelligence (AI) model that can use small amounts of linguistic data (gathered from clinical verbal cognition tests) to predict the onset of Alzheimer’s disease in healthy people with 71% accuracy.
The market’s expansion is aided by the ML platform’s numerous advantages. The platform, on the other hand, lacks a few essential components that are anticipated to impede market expansion. The market is severely constrained by the existence of imperfect and occasionally underdeveloped algorithms. Industrial businesses that make use of big data and machine learning need to be precise. Human intervention is required until the system has all parameters set and the error margin is close to or equal to zero. As a result, the expansion of the global machine learning market may be hampered by this feature.
The field of retail analytics has grown rapidly in recent years. Advanced data analytics technologies are utilized by numerous e-commerce businesses, including Alibaba, eBay, and Amazon, to boost sales and enhance customer satisfaction. The advancement of speech and voice recognition technologies has led to the development of cognitive speech coding methods based on ML principles.
Machine learning will become a significant trend in security analytics as businesses adopt more advanced security frameworks. Cybersecurity professionals have a difficult time tracking and analyzing potential cyberattacks because so much data is created and exchanged across multiple networks. As cyber threats become more widespread and complex, machine learning algorithms also help organizations and security teams anticipate, track, and recognize cyberattacks more quickly. Consequently, integrating advanced learning capabilities into analytics-driven solutions is unquestionably becoming a significant industry trend.
- IBM Corporation (New York, U.S.)
- SAP SE (Walldorf, Germany)
- Oracle Corporation (Texas, U.S.)
- Hewlett Packard Enterprise Company (Texas, U.S.)
- Microsoft Corporation (Washington, U.S.)
- Amazon, Inc. (Washington, U.S.)
- Intel Corporation (California, U.S.)
- Fair Isaac Corporation (California, U.S.)
- SAS Institute Inc. (North Carolina, U.S.)
- BigML, Inc. (Oregon, U.S.)
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