머신러닝 시장 - 세계 산업 규모, 점유율, 동향, 기회, 예측(2018-2028년), 컴포넌트별, 기업 규모별, 전개별, 최종사용자별 및 지역별 세분화

The Global Machine Learning Market is anticipated to grow at a robust pace in the forecast period 2022-2028. Technological innovation is the key strength behind the growth of the global machine-learning market. Artificial intelligence (AI) in machine learning (ML) enables computer programmers to forecast outcomes more accurately without being expressly trained. AI and machine learning are the newest boundaries for development and IT enterprises. Machine learning is an area of research focused on analyzing and developing "learning" processes and methods that use data to enhance efficiency on a given set of tasks.

Rising adoption of cloud-based services & ability to perform effectual output

Massive amounts of data can be reviewed by machine learning, which can identify trends and patterns that people would overlook. For instance, an e-commerce site like Amazon, knowing its customers' browsing patterns and past purchases, enables it to offer them the appropriate goods, discounts, and reminders. Furthermore, machine learning is used in part by ServiceNow, a cloud computing platform. The organization, which provides workflow software, employs machine learning to assist its clients in automating as many tedious procedures as possible and ensuring that staff members are working efficiently.

The ability to perform operations without involving human involvement, improvements in data center capabilities, and high computing power contribute to the technology's rise to prominence. Additionally, the market is expanding as a result of the quick adoption of cloud-based technologies in numerous sectors, such as Virtual services like software as a service (SaaS), platforms as a service (PaaS), and infrastructure as a service.

Machine Learning allows the identification of failures and their mitigation, directly affecting the standard and advancement of the process. Making errors enables process improvement. In addition to the ability for mistake and failure prevention, ML has stock prediction algorithms. Models built from data can forecast when an error may happen, enabling preventative measures to stop it from happening. This will likely cause the market to grow throughout the projected period.

Latest Trend of Self-Driving Vehicles and Multiple Handle Datasets

Companies are using this open-source artificial intelligence library to develop their machine-learning capabilities. For Instance, TensorFlow is library organizations use to build Java projects, data flow graphs, and various applications. APIs for Java are also present. For instance, Accenture Consultancy and professional services firms are using machine learning-based technologies with a market cap of USD 229 billion. Due to this market is expected to grow in the forecast period.

Many modern mobile devices can recognize autonomously when a user performs a certain activity, like cycling or running. Nowadays, novice machine learning engineers utilize a dataset that comprises fitness activity records for a few people that were acquired using mobile devices equipped with inertial sensors to practice with this sort of project. Furthermore, students are using categorization models that can precisely forecast future actions. Due to this, the adoption of machine learning in the datasets market is likely to increase in the forecast period.

ML is also being introduced in the automotive sector. For instance, Tesla, an American multinational company, announced the launch of self-driving. Although they have generated controversy, self-driving cars constitute one of the most remarkable advancements introduced in machine learning. This market is expected to grow with a high CAGR in the forecast period.

The machine-learning market has also expanded due to the integration of machine learning-in robots. For instance, Robot installations reached a new height in the United States in 2018, according to the statistics yearbook "World Robotics." Supporting they are using Line Follower Robot Using PID Algorithm due to which the Global machine learning market is expanding in the future.

Lack of skilled employees

However, the main difficulty most organizations have when integrating machine learning into their business processes is a lack of qualified workers with analytical talent, and there is an even greater need for those who can keep an eye on analytical material.

Market Segmentation

The Global Machine Learning Market is segmented into component, enterprise size, deployment, end-user, regional distribution, and competitive landscape. Based on components, the market is segmented into Services & Solutions. Based on enterprises' size, the market is divided into SMEs and large enterprises. Based on deployment, the market is divided into cloud and on-premises. Based on end-user, the market is divided into healthcare, retailer, it & telecom, automotive and transports, advertising & media, BFSI, government and defense, and others.

Market player

The main market players in the Global Machine Learning Market are Amazon Web Services, Inc., Baidu, Inc, Domino Data Lab, Inc, Microsoft Corporation, Google, Inc, Alpine Data, IBM Corporation, SAP SE, Intel Corporation, and SAS Institute Inc.

Recent Developments

• The use of DNN models for the early diagnosis and identification of diabetes and cardiac risk is now being worked on by NITI Aayog in India. The FDA is also developing a legal framework for utilizing AI and machine intelligence in the healthcare sector.
• Nvidia provides high-end video game graphics best, but the company's gamble on AI and machine learning has begun to pay off in recent years.
• The London-based firm Wayve raised USD200 million in January 2022. As a result, enterprises will be better equipped to train and build artificial intelligence capable of handling challenging driving situations.
• Accenture is a leading worldwide consulting organization and technology authority that frequently assists businesses in using technology to alter their operations. Machine learning is one of Accenture's various specialties.

Report Scope

In this report, Global Machine Learning Market has been segmented into the following categories, in addition to the industry trends, which have also been detailed below:

Machine Learning Market, By Component:

• Services
• Solutions

Machine Learning Market, By Enterprises Size:

• SMEs
• Large enterprises

Machine Learning Market, By Deployment:

• Cloud
• On-premises

Machine Learning Market, By End-user:

• Healthcare
• Retailer
• IT & telecom
• Automotive and Transports
• Advertising & Media
• BFSI
• Government and Defense
• Others

Machine Learning Market, By Region:

• North America
  • United States
  • Mexico
  • Canada

• Asia-Pacific
  • India
  • Japan
  • South Korea
  • Australia
  • Singapore
  • Malaysia
  • China

• Europe
  • Germany
  • United Kingdom
  • France
  • Italy
  • Spain
  • Poland
  • Denmark

• South America
  • Brazil
  • Argentina
  • Colombia
  • Peru
  • Chile

• Middle East
  • Saudi Arabia
  • South Africa
  • UAE
  • Iraq
  • Turkey

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Machine Learning Market.

Available Customizations

Global Machine Learning Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Service Overview

2. Research Methodology

3. Impact of COVID-19 Global Machine Learning Market

4. Executive Summary

5. Voice of Customers

6. Global Machine Learning Market

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Component (Services & Solutions)
  • 6.2.2. By Enterprises Size (SMEs and Large enterprises)
  • 6.2.3. By Deployment (Cloud and On-premises)
  • 6.2.4. By End-User (Healthcare, Retailer, IT & Telecom, Automotive and Transports, Advertising & Media, BFSI, Government and Defense and Others)
  • 6.2.5. By Region
• 6.3. By Company (2022)
• 6.4. Market Map

7. North America Machine Learning Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Component
  • 7.2.2. By Enterprises Size
  • 7.2.3. By Deployment
  • 7.2.4. By End-Use
  • 7.2.5. By Country
• 7.3. North America: Country Analysis
  • 7.3.1. United States Machine Learning Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Component
      • 7.3.1.2.2. By Enterprises Size
      • 7.3.1.2.3. By Deployment
      • 7.3.1.2.4. By End-Use
  • 7.3.2. Canada Machine Learning Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Component
      • 7.3.2.2.2. By Enterprises Size
      • 7.3.2.2.3. By Deployment
      • 7.3.2.2.4. By End-Use
  • 7.3.3. Mexico Machine Learning Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Component
      • 7.3.3.2.2. By Enterprises Size
      • 7.3.3.2.3. By Deployment
      • 7.3.3.2.4. By End-Use

8. Asia-Pacific Machine Learning Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Component
  • 8.2.2. By Enterprises Size
  • 8.2.3. By Deployment
  • 8.2.4. By End-Use
  • 8.2.5. By Country
• 8.3. Asia-Pacific: Country Analysis
  • 8.3.1. China Machine Learning Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Component
      • 8.3.1.2.2. By Enterprises Size
      • 8.3.1.2.3. By Deployment
      • 8.3.1.2.4. By End-Use
  • 8.3.2. India Machine Learning Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Component
      • 8.3.2.2.2. By Enterprises Size
      • 8.3.2.2.3. By Deployment
      • 8.3.2.2.4. By End-Use
  • 8.3.3. Japan Machine Learning Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Component
      • 8.3.3.2.2. By Enterprises Size
      • 8.3.3.2.3. By Deployment
      • 8.3.3.2.4. By End-Use
  • 8.3.4. South Korea Machine Learning Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Component
      • 8.3.4.2.2. By Enterprises Size
      • 8.3.4.2.3. By Deployment
      • 8.3.4.2.4. By End-Use
  • 8.3.5. Australia Machine Learning Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Component
      • 8.3.5.2.2. By Enterprises Size
      • 8.3.5.2.3. By Deployment
      • 8.3.5.2.4. By End-Use
  • 8.3.6. Singapore Machine Learning Market Outlook
    • 8.3.6.1. Market Size & Forecast
      • 8.3.6.1.1. By Value
    • 8.3.6.2. Market Share & Forecast
      • 8.3.6.2.1. By Component
      • 8.3.6.2.2. By Enterprises Size
      • 8.3.6.2.3. By Deployment
      • 8.3.6.2.4. By End-Use
  • 8.3.7. Malaysia Machine Learning Market Outlook
    • 8.3.7.1. Market Size & Forecast
      • 8.3.7.1.1. By Value
    • 8.3.7.2. Market Share & Forecast
      • 8.3.7.2.1. By Component
      • 8.3.7.2.2. By Enterprises Size
      • 8.3.7.2.3. By Deployment
      • 8.3.7.2.4. By End-Use

9. Europe Machine Learning Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Component
  • 9.2.2. By Enterprises Size
  • 9.2.3. By Deployment
  • 9.2.4. By End-Use
  • 9.2.5. By Country
• 9.3. Europe: Country Analysis
  • 9.3.1. Germany Machine Learning Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Component
      • 9.3.1.2.2. By Enterprises Size
      • 9.3.1.2.3. By Deployment
      • 9.3.1.2.4. By End-Use
  • 9.3.2. United Kingdom Machine Learning Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Component
      • 9.3.2.2.2. By Enterprises Size
      • 9.3.2.2.3. By Deployment
      • 9.3.2.2.4. By End-Use
  • 9.3.3. France Machine Learning Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Component
      • 9.3.3.2.2. By Enterprises Size
      • 9.3.3.2.3. By Deployment
      • 9.3.3.2.4. By End-Use
  • 9.3.4. Russia Machine Learning Market Outlook
    • 9.3.4.1. Market Size & Forecast
      • 9.3.4.1.1. By Value
    • 9.3.4.2. Market Share & Forecast
      • 9.3.4.2.1. By Component
      • 9.3.4.2.2. By Enterprises Size
      • 9.3.4.2.3. By Deployment
      • 9.3.4.2.4. By End-Use
  • 9.3.5. Spain Machine Learning Market Outlook
    • 9.3.5.1. Market Size & Forecast
      • 9.3.5.1.1. By Value
    • 9.3.5.2. Market Share & Forecast
      • 9.3.5.2.1. By Component
      • 9.3.5.2.2. By Enterprises Size
      • 9.3.5.2.3. By Deployment
      • 9.3.5.2.4. By End-Use
  • 9.3.6. Poland Machine Learning Market Outlook
    • 9.3.6.1. Market Size & Forecast
      • 9.3.6.1.1. By Value
    • 9.3.6.2. Market Share & Forecast
      • 9.3.6.2.1. By Component
      • 9.3.6.2.2. By Enterprises Size
      • 9.3.6.2.3. By Deployment
      • 9.3.6.2.4. By End-Use
  • 9.3.7. Italy Machine Learning Market Outlook
    • 9.3.7.1. Market Size & Forecast
      • 9.3.7.1.1. By Value
    • 9.3.7.2. Market Share & Forecast
      • 9.3.7.2.1. By Component
      • 9.3.7.2.2. By Enterprises Size
      • 9.3.7.2.3. By Deployment
      • 9.3.7.2.4. By End-Use
  • 9.3.8. Denmark Machine Learning Market Outlook
    • 9.3.8.1. Market Size & Forecast
      • 9.3.8.1.1. By Value
    • 9.3.8.2. Market Share & Forecast
      • 9.3.8.2.1. By Component
      • 9.3.8.2.2. By Enterprises Size
      • 9.3.8.2.3. By Deployment
      • 9.3.8.2.4. By End-Use

10. South America Machine Learning Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Component
  • 10.2.2. By Enterprises Size
  • 10.2.3. By Deployment
  • 10.2.4. By End-Use
  • 10.2.5. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil Machine Learning Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Component
      • 10.3.1.2.2. By Enterprises Size
      • 10.3.1.2.3. By Deployment
      • 10.3.1.2.4. By End-Use
  • 10.3.2. Argentina Machine Learning Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Component
      • 10.3.2.2.2. By Enterprises Size
      • 10.3.2.2.3. By Deployment
      • 10.3.2.2.4. By End-Use
  • 10.3.3. Colombia Machine Learning Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Component
      • 10.3.3.2.2. By Enterprises Size
      • 10.3.3.2.3. By Deployment
      • 10.3.3.2.4. By End-Use
  • 10.3.4. Peru Machine Learning Market Outlook
    • 10.3.4.1. Market Size & Forecast
      • 10.3.4.1.1. By Value
    • 10.3.4.2. Market Share & Forecast
      • 10.3.4.2.1. By Component
      • 10.3.4.2.2. By Enterprises Size
      • 10.3.4.2.3. By Deployment
      • 10.3.4.2.4. By End-Use
  • 10.3.5. Chile Machine Learning Market Outlook
    • 10.3.5.1. Market Size & Forecast
      • 10.3.5.1.1. By Value
    • 10.3.5.2. Market Share & Forecast
      • 10.3.5.2.1. By Component
      • 10.3.5.2.2. By Enterprises Size
      • 10.3.5.2.3. By Deployment
      • 10.3.5.2.4. By End-Use

11. Middle East & Africa Machine Learning Market Outlook

• 11.1. Market Size & Forecast
  • 11.1.1. By Value
• 11.2. Market Share & Forecast
  • 11.2.1. By Component
  • 11.2.2. By Enterprises Size
  • 11.2.3. By Deployment
  • 11.2.4. By End-Use
  • 11.2.5. By Country
• 11.3. Middle East & Africa: Country Analysis
  • 11.3.1. Saudi Arabia Machine Learning Market Outlook
    • 11.3.1.1. Market Size & Forecast
      • 11.3.1.1.1. By Value
    • 11.3.1.2. Market Share & Forecast
      • 11.3.1.2.1. By Component
      • 11.3.1.2.2. By Enterprises Size
      • 11.3.1.2.3. By Deployment
      • 11.3.1.2.4. By End-Use
  • 11.3.2. South Africa Machine Learning Market Outlook
    • 11.3.2.1. Market Size & Forecast
      • 11.3.2.1.1. By Value
    • 11.3.2.2. Market Share & Forecast
      • 11.3.2.2.1. By Component
      • 11.3.2.2.2. By Enterprises Size
      • 11.3.2.2.3. By Deployment
      • 11.3.2.2.4. By End-Use
  • 11.3.3. UAE Machine Learning Market Outlook
    • 11.3.3.1. Market Size & Forecast
      • 11.3.3.1.1. By Value
    • 11.3.3.2. Market Share & Forecast
      • 11.3.3.2.1. By Component
      • 11.3.3.2.2. By Enterprises Size
      • 11.3.3.2.3. By Deployment
      • 11.3.3.2.4. By End-Use
  • 11.3.4. Israel Machine Learning Market Outlook
    • 11.3.4.1. Market Size & Forecast
      • 11.3.4.1.1. By Value
    • 11.3.4.2. Market Share & Forecast
      • 11.3.4.2.1. By Component
      • 11.3.4.2.2. By Enterprises Size
      • 11.3.4.2.3. By Deployment
      • 11.3.4.2.4. By End-Use
  • 11.3.5. Turkey Machine Learning Market Outlook
    • 11.3.5.1. Market Size & Forecast
      • 11.3.5.1.1. By Value
    • 11.3.5.2. Market Share & Forecast
      • 11.3.5.2.1. By Component
      • 11.3.5.2.2. By Enterprises Size
      • 11.3.5.2.3. By Deployment
      • 11.3.5.2.4. By End-Use

12. Market Dynamics

• 12.1. Drivers
• 12.2. Challenges

13. Market Trends & Developments

14. Company Profiles

• 14.1. Amazon Web Services, Inc.
  • 14.1.1. Business Overview
  • 14.1.2. Key Revenue and Financials
  • 14.1.3. Recent Developments
  • 14.1.4. Key Personnel
  • 14.1.5. Key Product/Services
• 14.2. Baidu, Inc.
  • 14.2.1. Business Overview
  • 14.2.2. Key Revenue and Financials
  • 14.2.3. Recent Developments
  • 14.2.4. Key Personnel
  • 14.2.5. Key Product/Services
• 14.3. Domino Data Lab, Inc.
  • 14.3.1. Business Overview
  • 14.3.2. Key Revenue and Financials
  • 14.3.3. Recent Developments
  • 14.3.4. Key Personnel
  • 14.3.5. Key Product/Services
• 14.4. Microsoft Corporation
  • 14.4.1. Business Overview
  • 14.4.2. Key Revenue and Financials
  • 14.4.3. Recent Developments
  • 14.4.4. Key Personnel
  • 14.4.5. Key Product/Services
• 14.5. Google, Inc.
  • 14.5.1. Business Overview
  • 14.5.2. Key Revenue and Financials
  • 14.5.3. Recent Developments
  • 14.5.4. Key Personnel
  • 14.5.5. Key Product/Services
• 14.6. Alpine Data
  • 14.6.1. Business Overview
  • 14.6.2. Key Revenue and Financials
  • 14.6.3. Recent Developments
  • 14.6.4. Key Personnel
  • 14.6.5. Key Product/Services
• 14.7. IBM Corporation
  • 14.7.1. Business Overview
  • 14.7.2. Key Revenue and Financials
  • 14.7.3. Recent Developments
  • 14.7.4. Key Personnel
  • 14.7.5. Key Product/Services
• 14.8. SAP SE
  • 14.8.1. Business Overview
  • 14.8.2. Key Revenue and Financials
  • 14.8.3. Recent Developments
  • 14.8.4. Key Personnel
  • 14.8.5. Key Product/Services
• 14.9. Intel Corporation
  • 14.9.1. Business Overview
  • 14.9.2. Key Revenue and Financials
  • 14.9.3. Recent Developments
  • 14.9.4. Key Personnel
  • 14.9.5. Key Product/Services
• 14.10. SAS Institute Inc.
  • 14.10.1. Business Overview
  • 14.10.2. Key Revenue and Financials
  • 14.10.3. Recent Developments
  • 14.10.4. Key Personnel
  • 14.10.5. Key Product/Services

15. Strategic Recommendations

16. About Us & Disclaimer