Unsupervised Learning - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030

Publication ID:

PB510247057

Publication Date:

October 30, 2024

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 3,950.00

IT Services [2]

Computing & Electronics [3]

Description:

The global market for Unsupervised Learning was estimated to be worth US$ million in 2023 and is forecast to a readjusted size of US$ million by 2030 with a CAGR of % during the forecast period 2024-2030.
North American market for Unsupervised Learning was valued at $ million in 2023 and will reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Asia-Pacific market for Unsupervised Learning was valued at $ million in 2023 and will reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Europe market for Unsupervised Learning was valued at $ million in 2023 and will reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The global key companies of Unsupervised Learning include Microsoft, Fair Isaac, IBM, Amazon, Google, RapidMiner, TIBCO Software and H2o.AI, etc. In 2023, the global five largest players hold a share approximately % in terms of revenue.
Report Scope
This report aims to provide a comprehensive presentation of the global market for Unsupervised Learning, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Unsupervised Learning by region & country, by Type, and by Application.
The Unsupervised Learning market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Unsupervised Learning.
Market Segmentation
By Company
Microsoft
Fair Isaac
IBM
Amazon
Google
RapidMiner
TIBCO Software
H2o.AI
Segment by Type:
On-Premise
Cloud-Based
Segment by Application
Small and Medium Enterprises
Large Enterprises
By Region
North America
United States
Canada
Europe
Germany
France
U.K.
Italy
Russia
Asia-Pacific
China
Japan
South Korea
China Taiwan
Southeast Asia
India
Latin America
Mexico
Brazil
Argentina
Middle East & Africa
Turkey
Saudi Arabia
UAE
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Unsupervised Learning manufacturers competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Revenue of Unsupervised Learning in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Unsupervised Learning in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Market Overview
1.1 Unsupervised Learning Product Introduction
1.2 Global Unsupervised Learning Market Size Forecast
1.3 Unsupervised Learning Market Trends & Drivers
1.3.1 Unsupervised Learning Industry Trends
1.3.2 Unsupervised Learning Market Drivers & Opportunity
1.3.3 Unsupervised Learning Market Challenges
1.3.4 Unsupervised Learning Market Restraints
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Competitive Analysis by Company
2.1 Global Unsupervised Learning Players Revenue Ranking (2023)
2.2 Global Unsupervised Learning Revenue by Company (2019-2024)
2.3 Key Companies Unsupervised Learning Manufacturing Base Distribution and Headquarters
2.4 Key Companies Unsupervised Learning Product Offered
2.5 Key Companies Time to Begin Mass Production of Unsupervised Learning
2.6 Unsupervised Learning Market Competitive Analysis
2.6.1 Unsupervised Learning Market Concentration Rate (2019-2024)
2.6.2 Global 5 and 10 Largest Companies by Unsupervised Learning Revenue in 2023
2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Unsupervised Learning as of 2023)
2.7 Mergers & Acquisitions, Expansion
3 Segmentation by Type
3.1 Introduction by Type
3.1.1 On-Premise
3.1.2 Cloud-Based
3.2 Global Unsupervised Learning Sales Value by Type
3.2.1 Global Unsupervised Learning Sales Value by Type (2019 VS 2023 VS 2030)
3.2.2 Global Unsupervised Learning Sales Value, by Type (2019-2030)
3.2.3 Global Unsupervised Learning Sales Value, by Type (%) (2019-2030)
4 Segmentation by Application
4.1 Introduction by Application
4.1.1 Small and Medium Enterprises
4.1.2 Large Enterprises
4.2 Global Unsupervised Learning Sales Value by Application
4.2.1 Global Unsupervised Learning Sales Value by Application (2019 VS 2023 VS 2030)
4.2.2 Global Unsupervised Learning Sales Value, by Application (2019-2030)
4.2.3 Global Unsupervised Learning Sales Value, by Application (%) (2019-2030)
5 Segmentation by Region
5.1 Global Unsupervised Learning Sales Value by Region
5.1.1 Global Unsupervised Learning Sales Value by Region: 2019 VS 2023 VS 2030
5.1.2 Global Unsupervised Learning Sales Value by Region (2019-2024)
5.1.3 Global Unsupervised Learning Sales Value by Region (2025-2030)
5.1.4 Global Unsupervised Learning Sales Value by Region (%), (2019-2030)
5.2 North America
5.2.1 North America Unsupervised Learning Sales Value, 2019-2030
5.2.2 North America Unsupervised Learning Sales Value by Country (%), 2023 VS 2030
5.3 Europe
5.3.1 Europe Unsupervised Learning Sales Value, 2019-2030
5.3.2 Europe Unsupervised Learning Sales Value by Country (%), 2023 VS 2030
5.4 Asia Pacific
5.4.1 Asia Pacific Unsupervised Learning Sales Value, 2019-2030
5.4.2 Asia Pacific Unsupervised Learning Sales Value by Country (%), 2023 VS 2030
5.5 South America
5.5.1 South America Unsupervised Learning Sales Value, 2019-2030
5.5.2 South America Unsupervised Learning Sales Value by Country (%), 2023 VS 2030
5.6 Middle East & Africa
5.6.1 Middle East & Africa Unsupervised Learning Sales Value, 2019-2030
5.6.2 Middle East & Africa Unsupervised Learning Sales Value by Country (%), 2023 VS 2030
6 Segmentation by Key Countries/Regions
6.1 Key Countries/Regions Unsupervised Learning Sales Value Growth Trends, 2019 VS 2023 VS 2030
6.2 Key Countries/Regions Unsupervised Learning Sales Value
6.3 United States
6.3.1 United States Unsupervised Learning Sales Value, 2019-2030
6.3.2 United States Unsupervised Learning Sales Value by Type (%), 2023 VS 2030
6.3.3 United States Unsupervised Learning Sales Value by Application, 2023 VS 2030
6.4 Europe
6.4.1 Europe Unsupervised Learning Sales Value, 2019-2030
6.4.2 Europe Unsupervised Learning Sales Value by Type (%), 2023 VS 2030
6.4.3 Europe Unsupervised Learning Sales Value by Application, 2023 VS 2030
6.5 China
6.5.1 China Unsupervised Learning Sales Value, 2019-2030
6.5.2 China Unsupervised Learning Sales Value by Type (%), 2023 VS 2030
6.5.3 China Unsupervised Learning Sales Value by Application, 2023 VS 2030
6.6 Japan
6.6.1 Japan Unsupervised Learning Sales Value, 2019-2030
6.6.2 Japan Unsupervised Learning Sales Value by Type (%), 2023 VS 2030
6.6.3 Japan Unsupervised Learning Sales Value by Application, 2023 VS 2030
6.7 South Korea
6.7.1 South Korea Unsupervised Learning Sales Value, 2019-2030
6.7.2 South Korea Unsupervised Learning Sales Value by Type (%), 2023 VS 2030
6.7.3 South Korea Unsupervised Learning Sales Value by Application, 2023 VS 2030
6.8 Southeast Asia
6.8.1 Southeast Asia Unsupervised Learning Sales Value, 2019-2030
6.8.2 Southeast Asia Unsupervised Learning Sales Value by Type (%), 2023 VS 2030
6.8.3 Southeast Asia Unsupervised Learning Sales Value by Application, 2023 VS 2030
6.9 India
6.9.1 India Unsupervised Learning Sales Value, 2019-2030
6.9.2 India Unsupervised Learning Sales Value by Type (%), 2023 VS 2030
6.9.3 India Unsupervised Learning Sales Value by Application, 2023 VS 2030
7 Company Profiles
7.1 Microsoft
7.1.1 Microsoft Profile
7.1.2 Microsoft Main Business
7.1.3 Microsoft Unsupervised Learning Products, Services and Solutions
7.1.4 Microsoft Unsupervised Learning Revenue (US$ Million) & (2019-2024)
7.1.5 Microsoft Recent Developments
7.2 Fair Isaac
7.2.1 Fair Isaac Profile
7.2.2 Fair Isaac Main Business
7.2.3 Fair Isaac Unsupervised Learning Products, Services and Solutions
7.2.4 Fair Isaac Unsupervised Learning Revenue (US$ Million) & (2019-2024)
7.2.5 Fair Isaac Recent Developments
7.3 IBM
7.3.1 IBM Profile
7.3.2 IBM Main Business
7.3.3 IBM Unsupervised Learning Products, Services and Solutions
7.3.4 IBM Unsupervised Learning Revenue (US$ Million) & (2019-2024)
7.3.5 Amazon Recent Developments
7.4 Amazon
7.4.1 Amazon Profile
7.4.2 Amazon Main Business
7.4.3 Amazon Unsupervised Learning Products, Services and Solutions
7.4.4 Amazon Unsupervised Learning Revenue (US$ Million) & (2019-2024)
7.4.5 Amazon Recent Developments
7.5 Google
7.5.1 Google Profile
7.5.2 Google Main Business
7.5.3 Google Unsupervised Learning Products, Services and Solutions
7.5.4 Google Unsupervised Learning Revenue (US$ Million) & (2019-2024)
7.5.5 Google Recent Developments
7.6 RapidMiner
7.6.1 RapidMiner Profile
7.6.2 RapidMiner Main Business
7.6.3 RapidMiner Unsupervised Learning Products, Services and Solutions
7.6.4 RapidMiner Unsupervised Learning Revenue (US$ Million) & (2019-2024)
7.6.5 RapidMiner Recent Developments
7.7 TIBCO Software
7.7.1 TIBCO Software Profile
7.7.2 TIBCO Software Main Business
7.7.3 TIBCO Software Unsupervised Learning Products, Services and Solutions
7.7.4 TIBCO Software Unsupervised Learning Revenue (US$ Million) & (2019-2024)
7.7.5 TIBCO Software Recent Developments
7.8 H2o.AI
7.8.1 H2o.AI Profile
7.8.2 H2o.AI Main Business
7.8.3 H2o.AI Unsupervised Learning Products, Services and Solutions
7.8.4 H2o.AI Unsupervised Learning Revenue (US$ Million) & (2019-2024)
7.8.5 H2o.AI Recent Developments
8 Industry Chain Analysis
8.1 Unsupervised Learning Industrial Chain
8.2 Unsupervised Learning Upstream Analysis
8.2.1 Key Raw Materials
8.2.2 Raw Materials Key Suppliers
8.2.3 Manufacturing Cost Structure
8.3 Midstream Analysis
8.4 Downstream Analysis (Customers Analysis)
8.5 Sales Model and Sales Channels
8.5.1 Unsupervised Learning Sales Model
8.5.2 Sales Channel
8.5.3 Unsupervised Learning Distributors
9 Research Findings and Conclusion
10 Appendix
10.1 Research Methodology
10.1.1 Methodology/Research Approach
10.1.2 Data Source
10.2 Author Details
10.3 Disclaimer

Companies Mentioned:

Microsoft
Fair Isaac
IBM
Amazon
Google
RapidMiner
TIBCO Software
H2o.AI

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