Subscribe Us

header ads

Recents

header ads

Machine Learning as a Service Market Size At Around US$ 305.62 Bn In 2030

The machine learning as a service market would grow at a CAGR of 39.3% over the predicted time frame. The market is expected to increase in value from US$ 21.55 Bn in 2022 to US$ 305.62 Bn in 2030.

Machine Learning as a Service Market Size 2022 To 2030

The on machine learning as a service Market, which provides a business strategy, research & development activities, concise outline of the market valuation, valuable insights pertaining to market share, size, supply chain analysis, competitive landscape and regional proliferation of this industry.

Download Free Sample@ https://www.precedenceresearch.com/sample/2023

Report Scope of the Machine Learning as a Service Market

Report CoverageDetails
Market Size in 2022

USD 21.55 Billion

Market Size by 2030

USD 305.62 Billion

Growth Rate from 2022 to 2030CAGR of 39.3%
Base Year2021
Forecast Period2022 to 2030
Segments CoveredComponent, Organization Size, Application, Industry Vertical, Geography

A recent report provides crucial insights along with application based and forecast information in the Global Machine learning as a service Market. The report provides a comprehensive analysis of key factors that are expected to drive the growth of this market. This study also provides a detailed overview of the opportunities along with the current trends observed in the Machine learning as a service market.

A quantitative analysis of the industry is compiled for a period of 10 years in order to assist players to grow in the market. Insights on specific revenue figures generated are also given in the report, along with projected revenue at the end of the forecast period.

Companies and Manufacturers Covered

The study covers key players operating in the market along with prime schemes and strategies implemented by each player to hold high positions in the industry. Such a tough vendor landscape provides a competitive outlook of the industry, consequently existing as a key insight. These insights were thoroughly analysed and prime business strategies and products that offer high revenue generation capacities were identified. Key players of the global Machine learning as a service market are included as given below:

Machine learning as a service Market Key Players

  • GOOGLE INC
  • SAS INSTITUTE INC
  • FICO
  • HEWLETT PACKARD ENTERPRISE
  • YOTTAMINE ANALYTICS
  • AMAZON WEB SERVICES
  • BIGML, INC
  • MICROSOFT CORPORATION
  • PREDICTRON LABS LTD
  • IBM CORPORATION

Market Segments

By Component

  • Solution
  • Services

By Organization Size

  • Small and Medium-Sized Enterprises
  • Large Enterprises

By Application

  • Marketing & Advertising
  • Fraud Detection & Risk Management
  • Computer vision
  • Security & Surveillance
  • Predictive analytics
  • Natural Language Processing
  • Augmented & Virtual Reality
  • Others

By Industry Vertical

  • BFSI
  • IT & Telecom
  • Automotive
  • Healthcare
  • Aerospace & Defense
  • Retail
  • Government
  • Others

By Geography

  • North America
    • U.S.
    • Canada
  • Europe
    • U.K.
    • Germany
    • France
  • Asia-Pacific
    • China
    • India
    • Japan
    • South Korea
    • Malaysia
    • Philippines
  • Latin America
    • Brazil
    • Rest of Latin America
  • Middle East & Africa (MEA)

Report Objectives

  • To define, describe, and forecast the global machine learning as a service market based on product, and region
  • To provide detailed information regarding the major factors influencing the growth of the market (drivers, opportunities, and industry-specific challenges)
  • To strategically analyze micromarkets1 with respect to individual growth trends, future prospects, and contributions to the total market
  • To analyze opportunities in the market for stakeholders and provide details of the competitive landscape for market leaders
  • To forecast the size of market segments with respect to four main regions—North America, Europe, Asia Pacific and the Rest of the World (RoW)2
  • To strategically profile key players and comprehensively analyze their product portfolios, market shares, and core competencies3
  • To track and analyze competitive developments such as acquisitions, expansions, new product launches, and partnerships in the machine learning as a service market

Table of Content

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Machine Learning as a Service Market 

5.1. COVID-19 Landscape: Machine Learning as a Service Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Machine Learning as a Service Market, By Component

8.1. Machine Learning as a Service Market, by Component, 2022-2030

8.1.1. Solution

8.1.1.1. Market Revenue and Forecast (2017-2030)

8.1.2. Services

8.1.2.1. Market Revenue and Forecast (2017-2030)

Chapter 9. Global Machine Learning as a Service Market, By Organization Size

9.1. Machine Learning as a Service Market, by Organization Size e, 2022-2030

9.1.1. Small and Medium-Sized Enterprises

9.1.1.1. Market Revenue and Forecast (2017-2030)

9.1.2. Large Enterprises

9.1.2.1. Market Revenue and Forecast (2017-2030)

Chapter 10. Global Machine Learning as a Service Market, By Application 

10.1. Machine Learning as a Service Market, by Application, 2022-2030

10.1.1. Marketing & Advertising

10.1.1.1. Market Revenue and Forecast (2017-2030)

10.1.2. Fraud Detection & Risk Management

10.1.2.1. Market Revenue and Forecast (2017-2030)

10.1.3. Computer vision

10.1.3.1. Market Revenue and Forecast (2017-2030)

10.1.4. Security & Surveillance

10.1.4.1. Market Revenue and Forecast (2017-2030)

10.1.5. Predictive analytics

10.1.5.1. Market Revenue and Forecast (2017-2030)

10.1.6. Natural Language Processing

10.1.6.1. Market Revenue and Forecast (2017-2030)

10.1.7. Augmented & Virtual Reality

10.1.7.1. Market Revenue and Forecast (2017-2030)

10.1.8. Others

10.1.8.1. Market Revenue and Forecast (2017-2030)

Chapter 11. Global Machine Learning as a Service Market, By Industry Vertical 

11.1. Machine Learning as a Service Market, by Industry Vertical, 2022-2030

11.1.1. BFSI

11.1.1.1. Market Revenue and Forecast (2017-2030)

11.1.2. IT & Telecom

11.1.2.1. Market Revenue and Forecast (2017-2030)

11.1.3. Automotive

11.1.3.1. Market Revenue and Forecast (2017-2030)

11.1.4. Healthcare

11.1.4.1. Market Revenue and Forecast (2017-2030)

11.1.5. Aerospace & Defense

11.1.5.1. Market Revenue and Forecast (2017-2030)

11.1.6. Retail

11.1.6.1. Market Revenue and Forecast (2017-2030)

11.1.7. Government

11.1.7.1. Market Revenue and Forecast (2017-2030)

11.1.8. Others

11.1.8.1. Market Revenue and Forecast (2017-2030)

Chapter 12. Global Machine Learning as a Service Market, Regional Estimates and Trend Forecast

12.1. North America

12.1.1. Market Revenue and Forecast, by Component (2017-2030)

12.1.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.1.3. Market Revenue and Forecast, by Application (2017-2030)

12.1.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.1.5. U.S.

12.1.5.1. Market Revenue and Forecast, by Component (2017-2030)

12.1.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.1.5.3. Market Revenue and Forecast, by Application (2017-2030)

12.1.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.1.6. Rest of North America

12.1.6.1. Market Revenue and Forecast, by Component (2017-2030)

12.1.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.1.6.3. Market Revenue and Forecast, by Application (2017-2030)

12.1.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.2. Europe

12.2.1. Market Revenue and Forecast, by Component (2017-2030)

12.2.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.2.3. Market Revenue and Forecast, by Application (2017-2030)

12.2.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.2.5. UK

12.2.5.1. Market Revenue and Forecast, by Component (2017-2030)

12.2.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.2.5.3. Market Revenue and Forecast, by Application (2017-2030)

12.2.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.2.6. Germany

12.2.6.1. Market Revenue and Forecast, by Component (2017-2030)

12.2.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.2.6.3. Market Revenue and Forecast, by Application (2017-2030)

12.2.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.2.7. France

12.2.7.1. Market Revenue and Forecast, by Component (2017-2030)

12.2.7.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.2.7.3. Market Revenue and Forecast, by Application (2017-2030)

12.2.7.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.2.8. Rest of Europe

12.2.8.1. Market Revenue and Forecast, by Component (2017-2030)

12.2.8.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.2.8.3. Market Revenue and Forecast, by Application (2017-2030)

12.2.8.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.3. APAC

12.3.1. Market Revenue and Forecast, by Component (2017-2030)

12.3.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.3.3. Market Revenue and Forecast, by Application (2017-2030)

12.3.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.3.5. India

12.3.5.1. Market Revenue and Forecast, by Component (2017-2030)

12.3.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.3.5.3. Market Revenue and Forecast, by Application (2017-2030)

12.3.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.3.6. China

12.3.6.1. Market Revenue and Forecast, by Component (2017-2030)

12.3.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.3.6.3. Market Revenue and Forecast, by Application (2017-2030)

12.3.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.3.7. Japan

12.3.7.1. Market Revenue and Forecast, by Component (2017-2030)

12.3.7.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.3.7.3. Market Revenue and Forecast, by Application (2017-2030)

12.3.7.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.3.8. Rest of APAC

12.3.8.1. Market Revenue and Forecast, by Component (2017-2030)

12.3.8.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.3.8.3. Market Revenue and Forecast, by Application (2017-2030)

12.3.8.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.4. MEA

12.4.1. Market Revenue and Forecast, by Component (2017-2030)

12.4.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.4.3. Market Revenue and Forecast, by Application (2017-2030)

12.4.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.4.5. GCC

12.4.5.1. Market Revenue and Forecast, by Component (2017-2030)

12.4.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.4.5.3. Market Revenue and Forecast, by Application (2017-2030)

12.4.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.4.6. North Africa

12.4.6.1. Market Revenue and Forecast, by Component (2017-2030)

12.4.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.4.6.3. Market Revenue and Forecast, by Application (2017-2030)

12.4.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.4.7. South Africa

12.4.7.1. Market Revenue and Forecast, by Component (2017-2030)

12.4.7.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.4.7.3. Market Revenue and Forecast, by Application (2017-2030)

12.4.7.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.4.8. Rest of MEA

12.4.8.1. Market Revenue and Forecast, by Component (2017-2030)

12.4.8.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.4.8.3. Market Revenue and Forecast, by Application (2017-2030)

12.4.8.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.5. Latin America

12.5.1. Market Revenue and Forecast, by Component (2017-2030)

12.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.5.3. Market Revenue and Forecast, by Application (2017-2030)

12.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.5.5. Brazil

12.5.5.1. Market Revenue and Forecast, by Component (2017-2030)

12.5.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.5.5.3. Market Revenue and Forecast, by Application (2017-2030)

12.5.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

12.5.6. Rest of LATAM

12.5.6.1. Market Revenue and Forecast, by Component (2017-2030)

12.5.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)

12.5.6.3. Market Revenue and Forecast, by Application (2017-2030)

12.5.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)

Chapter 13. Company Profiles

13.1. GOOGLE INC

13.1.1. Company Overview

13.1.2. Product Offerings

13.1.3. Financial Performance

13.1.4. Recent Initiatives

13.2. SAS INSTITUTE INC

13.2.1. Company Overview

13.2.2. Product Offerings

13.2.3. Financial Performance

13.2.4. Recent Initiatives

13.3. FICO

13.3.1. Company Overview

13.3.2. Product Offerings

13.3.3. Financial Performance

13.3.4. Recent Initiatives

13.4. HEWLETT PACKARD ENTERPRISE

13.4.1. Company Overview

13.4.2. Product Offerings

13.4.3. Financial Performance

13.4.4. Recent Initiatives

13.5. YOTTAMINE ANALYTICS

13.5.1. Company Overview

13.5.2. Product Offerings

13.5.3. Financial Performance

13.5.4. Recent Initiatives

13.6. AMAZON WEB SERVICES

13.6.1. Company Overview

13.6.2. Product Offerings

13.6.3. Financial Performance

13.6.4. Recent Initiatives

13.7. BIGML, INC

13.7.1. Company Overview

13.7.2. Product Offerings

13.7.3. Financial Performance

13.7.4. Recent Initiatives

13.8. MICROSOFT CORPORATION

13.8.1. Company Overview

13.8.2. Product Offerings

13.8.3. Financial Performance

13.8.4. Recent Initiatives

13.9. PREDICTRON LABS LTD

13.9.1. Company Overview

13.9.2. Product Offerings

13.9.3. Financial Performance

13.9.4. Recent Initiatives

13.10. IBM

13.10.1. Company Overview

13.10.2. Product Offerings

13.10.3. Financial Performance

13.10.4. Recent Initiatives

Chapter 14. Research Methodology

14.1. Primary Research

14.2. Secondary Research

14.3. Assumptions

Chapter 15. Appendix

15.1. About Us

15.2. Glossary of Terms

Contact Us:

Precedence Research

Apt 1408 1785 Riverside Drive Ottawa, ON, K1G 3T7, Canada

Call: +1 774 402 6168

Email: sales@precedenceresearch.com

Website: https://www.precedenceresearch.com

 Blog: https://www.pharma-geek.com

 

Post a Comment

0 Comments