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Report Description

The Global Machine Learning (ML) 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 for the preventative measures to stop it from happening. This will likely cause the market to grow throughout the projected period.


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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 (ML) Market is segmented into component, enterprises size, deployment, end-user, regional distribution and competitive landscape. Based on component, 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 ML Market are Amazon Web Services, Inc. Baidu, Inc, Domino Data Lab, Inc, Microsoft Corporation, Google, Inc, Alpine Data, IBM Corporation, SAP SE, Intel Corporation, 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.

Attribute

Details

Base Year

2022

Historic Data

2018– 2021

Estimated Year

2023

Forecast Period

2024 – 2028

Quantitative Units

Revenue in USD Million,  and CAGR for 2018-2022and 2023-2028

Report coverage

Revenue forecast, company share, growth factors, and trends

Segments covered

Component

Enterprises size

Deployment

End-user

Regional scope

North America; Asia-Pacific; Europe; South America; Middle East

Country scope

United States; Canada; Mexico; China; Indian; Japan; South Korea; Australia; Singapore; Malaysia; Germany; United Kingdom; France; Italy; Spain; Poland; Colombia; Brazil; Argentina; Peru; Chile; Africa, Saudi Arabia; South Africa; UAE; Iraq; Turkey

Key companies profiled

Amazon Web Services, Inc. Baidu, Inc, Domino Data Lab, Inc, Microsoft Corporation, Google, Inc, Alpine Data, IBM Corporation, SAP SE, Intel Corporation, SAS Institute Inc.

Customisation scope

10% free report customisation with purchase. Addition or alteration to country, regional & segment scope.

Pricing and purchase options

Avail customised purchase options to meet your exact research needs. Explore purchase options

Delivery Format

PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request)

 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:

        o    Machine Learning (ML) Market, By Component:

o   Services

o   Solutions

        o   Machine Learning (ML) Market, By Enterprises Size:

o   SMEs

o   Large enterprises

        o    Machine Learning (ML) Market, By Deployment:

o   Cloud

o   On-premises

        o    Machine Learning (ML) Market, By End-user:

o   Healthcare

o   Retailer

o   IT & telecom

o   Automotive and Transports

o   Advertising & Media

o   BFSI

o   Government and Defense

o   Others

        o    Machine Learning (ML) Market, By Region:

o   North America

§  United States

§  Mexico

§  Canada

o   Asia-Pacific

§  India

§  Japan

§  South Korea

§  Australia

§  Singapore

§  Malayasia

§  China

o   Europe

§  Germany

§  United Kingdom

§  France

§  Italy

§  Spain

§  Poland

§  Denmark

o   South America

§  Brazil

§  Argentina

§  Colombia

§  Peru

§  Chile

o   Middle East

§  South Arabia

§  South Africa

§  UAE

§  Iraq

§  Turkey 

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Machine Learning (ML) 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).

The Global Machine Learning (ML) Market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at [email protected]

Table of content

Table of content

1.    Service Overview

2.    Research Methodology

3.    Impact of COVID-19 Global Machine Learning Market

4.    Executive Summary

5.    Voice of Customers

5.1.  Brand Awareness

5.2.  Factors Considered while Selecting Vendor

5.3.  Key Satisfaction Level

5.4.  Major Challenges Faced

5.5.  Technological Awareness

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

6.2.6.                By Company

6.3.  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

8.4.  China Machine Learning Market Outlook

8.5.  Market Size & Forecast

8.5.1.1.1.           By Value 

8.5.1.2.        Market Share & Forecast

8.5.1.2.1.           By Component

8.5.1.2.2.           By Enterprises Size

8.5.1.2.3.           By Deployment

8.5.1.2.4.           By End-Use

8.5.2.                India Machine Learning Market Outlook

8.5.2.1.        Market Size & Forecast

8.5.2.1.1.           By Value 

8.5.2.2.        Market Share & Forecast

8.5.2.2.1.           By Component

8.5.2.2.2.           By Enterprises Size

8.5.2.2.3.           By Deployment

8.5.2.2.4.           By End-Use

8.5.3.                Japan Machine Learning Market Outlook

8.5.3.1.        Market Size & Forecast

8.5.3.1.1.           By Value 

8.5.3.2.        Market Share & Forecast

8.5.3.2.1.           By Component

8.5.3.2.2.           By Enterprises Size

8.5.3.2.3.           By Deployment

8.5.3.2.4.           By End-Use

8.5.4.                South Korea Machine Learning Market Outlook

8.5.4.1.        Market Size & Forecast

8.5.4.1.1.           By Value 

8.5.4.2.        Market Share & Forecast

8.5.4.2.1.           By Component

8.5.4.2.2.           By Enterprises Size

8.5.4.2.3.           By Deployment

8.5.4.2.4.           By End-Use

8.5.5.                Australia Machine Learning Market Outlook

8.5.5.1.        Market Size & Forecast

8.5.5.1.1.           By Value 

8.5.5.2.        Market Share & Forecast

8.5.5.2.1.           By Component

8.5.5.2.2.           By Enterprises Size

8.5.5.2.3.           By Deployment

8.5.5.2.4.           By End-Use

8.5.6.                Singapore Machine Learning Market Outlook

8.5.6.1.        Market Size & Forecast

8.5.6.1.1.           By Value 

8.5.6.2.        Market Share & Forecast

8.5.6.2.1.           By Component

8.5.6.2.2.           By Enterprises Size

8.5.6.2.3.           By Deployment

8.5.6.2.4.           By End-Use

8.5.7.                Malaysia Machine Learning Market Outlook

8.5.7.1.        Market Size & Forecast

8.5.7.1.1.           By Value 

8.5.7.2.        Market Share & Forecast

8.5.7.2.1.           By Component

8.5.7.2.2.           By Enterprises Size

8.5.7.2.3.           By Deployment

8.5.7.2.4.           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

9.4.  South America: Country Analysis

9.4.1.                Brazil Machine Learning Market Outlook

9.4.1.1.        Market Size & Forecast

9.4.1.1.1.           By Value 

9.4.1.2.        Market Share & Forecast

9.4.1.2.1.           By Component

9.4.1.2.2.           By Enterprises Size

9.4.1.2.3.           By Deployment

9.4.1.2.4.           By End-Use

9.4.2.                Argentina Machine Learning Market Outlook

9.4.2.1.        Market Size & Forecast

9.4.2.1.1.           By Value 

9.4.2.2.        Market Share & Forecast

9.4.2.2.1.           By Component

9.4.2.2.2.           By Enterprises Size

9.4.2.2.3.           By Deployment

9.4.2.2.4.           By End-Use

9.4.3.                Colombia Machine Learning Market Outlook

9.4.3.1.        Market Size & Forecast

9.4.3.1.1.           By Value 

9.4.3.2.        Market Share & Forecast

9.4.3.2.1.           By Component

9.4.3.2.2.           By Enterprises Size

9.4.3.2.3.           By Deployment

9.4.3.2.4.           By End-Use

9.4.4.                Peru Machine Learning Market Outlook

9.4.4.1.        Market Size & Forecast

9.4.4.1.1.           By Value 

9.4.4.2.        Market Share & Forecast

9.4.4.2.1.           By Component

9.4.4.2.2.           By Enterprises Size

9.4.4.2.3.           By Deployment

9.4.4.2.4.           By End-Use

9.4.5.                Chile Machine Learning Market Outlook

9.4.5.1.        Market Size & Forecast

9.4.5.1.1.           By Value 

9.4.5.2.        Market Share & Forecast

9.4.5.2.1.           By Component

9.4.5.2.2.           By Enterprises Size

9.4.5.2.3.           By Deployment

9.4.5.2.4.           By End-Use

10. Middle East & Africa 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.   Middle East & Africa: Country Analysis

10.3.1.             Saudi 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 Product Type

10.3.1.2.2.         By Capacity

10.3.1.2.3.         By End-Use

10.3.2.             South Africa 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.             UAE 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.             Israel 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.             Turkey 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. Market Dynamics

11.1.   Drivers

11.1.1.             Advancement in technologies

11.1.2.             Companies moving towards ML technologies to handle multiple data sets

11.1.3.             Less human effort and effectual output

11.1.4.             Rising cloud-based services

11.1.5.             Ability to perform effective output

11.2.   Challenges

11.2.1.             Lack of skilled employee

11.2.2.             Multiple data handle at the same time

12. Market Trends & Developments

12.1.   Adoption of Self-driving cars

12.2.   The integration of machine learning in robotics

12.3.   Usage of open-source artificial intelligence library

12.4.   Modern mobile devices image recognization

13. Company Profiles

13.1.   Amazon Web Services, Inc.

13.1.1.             Business Overview

13.1.2.             Key Revenue and Financials

13.1.3.             Recent Developments

13.1.4.             Key Personnel

13.1.5.             Key Product/Services

13.1.6.             SWOT Analysis

13.2.   Baidu, Inc.

13.2.1.             Business Overview

13.2.2.             Key Revenue and Financials

13.2.3.             Recent Developments

13.2.4.             Key Personnel

13.2.5.             Key Product/Services

13.2.6.             SWOT Analysis

13.3.   Domino Data Lab, Inc.

13.3.1.             Business Overview

13.3.2.             Key Revenue and Financials

13.3.3.             Recent Developments

13.3.4.             Key Personnel

13.3.5.             Key Product/Services

13.3.6.             SWOT Analysis

13.4.   Microsoft Corporation

13.4.1.             Business Overview

13.4.2.             Key Revenue and Financials

13.4.3.             Recent Developments

13.4.4.             Key Personnel

13.4.5.             Key Product/Services

13.4.6.             SWOT Analysis

13.5.   Google, Inc.

13.5.1.             Business Overview

13.5.2.             Key Revenue and Financials

13.5.3.             Recent Developments

13.5.4.             Key Personnel

13.5.5.             Key Product/Services

13.5.6.             SWOT Analysis

13.6.   Alpine Data

13.6.1.             Business Overview

13.6.2.             Key Revenue and Financials

13.6.3.             Recent Developments

13.6.4.             Key Personnel

13.6.5.             Key Product/Services

13.6.6.             SWOT Analysis 

13.7.   IBM Corporation

13.7.1.             Business Overview

13.7.2.             Key Revenue and Financials

13.7.3.             Recent Developments

13.7.4.             Key Personnel

13.7.5.             Key Product/Services

13.7.6.             SWOT Analysis

13.8.   SAP SE

13.8.1.             Business Overview

13.8.2.             Key Revenue and Financials

13.8.3.             Recent Developments

13.8.4.             Key Personnel

13.8.5.             Key Product/Services

13.8.6.             SWOT Analysis

13.9.   Intel Corporation

13.9.1.             Business Overview

13.9.2.             Key Revenue and Financials

13.9.3.             Recent Developments

13.9.4.             Key Personnel

13.9.5.             Key Product/Services

13.9.6.             SWOT Analysis

13.10.SAS Institute Inc.

13.10.1.          Business Overview

13.10.2.          Key Revenue and Financials

13.10.3.          Recent Developments

13.10.4.          Key Personnel

13.10.5.          Key Product/Services

13.10.6.          SWOT Analysis 

14. Strategic Recommendations

14.1.   Key focus on latest technology

14.2.   Major focus on north America region

15. About Us & Disclaimer

Figures and Tables

Frequently asked questions

Frequently asked questions

Machine learning is an area of research focused on comprehending and developing "learning" processes that use data to enhance performance on tasks. It is considered to be a component of artificial intelligence.

Image recognition is a well-known and common application of machine learning in the real world. It can recognize an item as a digital image based on the intensity of the pixels in black-and-white or color photos.

Supervised, unsupervised, and reinforcement learning are the three categories of machine learning.

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, SAS Institute Inc.

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