Machine learning tools are algorithmic applications of artificial intelligence that give systems the ability to learn and improve without ample human input; similar concepts are data mining and predictive modeling. They allow software to become more accurate in predicting outcomes without being explicitly programmed. The idea is that a model or algorithm is used to get data from the world, and that data is fed back into the model so that it improves over time. It鈥檚 called听machine learning听because the model 鈥渓earns鈥� as it is fed more and more data.
The global Machine Learning Tools market was valued at US$ million in 2023 and is anticipated to reach US$ million by 2030, witnessing a CAGR of % during the forecast period 2024-2030.
North American market for Machine Learning Tools is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Asia-Pacific market for Machine Learning Tools is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The global market for Machine Learning Tools in Manufacturing is estimated to increase from $ million in 2023 to $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The major global companies of Machine Learning Tools include Microsoft, IBM, Google, RStudio, Amazon, Oracle, Meta Platforms, Kira and Databricks, etc. In 2023, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for Machine Learning Tools, 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 Machine Learning Tools.
Report Scope
The Machine Learning Tools market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Machine Learning Tools market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Machine Learning Tools companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
Microsoft
IBM
Google
RStudio
Amazon
Oracle
Meta Platforms
Kira
Databricks
DataRobot
OpenText
Scikit-learn
Catalyst
XGBoost
LightGBM
Segment by Type
On-Premise
Cloud-Based
Segment by Application
Manufacturing
Retail
Agriculture
Healthcare
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Machine Learning Tools companies鈥� competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: 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 5: 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 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Machine Learning Tools Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 On-Premise
1.2.3 Cloud-Based
1.3 Market by Application
1.3.1 Global Machine Learning Tools Market Growth by Application: 2019 VS 2023 VS 2030
1.3.2 Manufacturing
1.3.3 Retail
1.3.4 Agriculture
1.3.5 Healthcare
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Machine Learning Tools Market Perspective (2019-2030)
2.2 Machine Learning Tools Growth Trends by Region
2.2.1 Global Machine Learning Tools Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Machine Learning Tools Historic Market Size by Region (2019-2024)
2.2.3 Machine Learning Tools Forecasted Market Size by Region (2025-2030)
2.3 Machine Learning Tools Market Dynamics
2.3.1 Machine Learning Tools Industry Trends
2.3.2 Machine Learning Tools Market Drivers
2.3.3 Machine Learning Tools Market Challenges
2.3.4 Machine Learning Tools Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Machine Learning Tools Players by Revenue
3.1.1 Global Top Machine Learning Tools Players by Revenue (2019-2024)
3.1.2 Global Machine Learning Tools Revenue Market Share by Players (2019-2024)
3.2 Global Machine Learning Tools Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Machine Learning Tools Revenue
3.4 Global Machine Learning Tools Market Concentration Ratio
3.4.1 Global Machine Learning Tools Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Machine Learning Tools Revenue in 2023
3.5 Machine Learning Tools Key Players Head office and Area Served
3.6 Key Players Machine Learning Tools Product Solution and Service
3.7 Date of Enter into Machine Learning Tools Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Machine Learning Tools Breakdown Data by Type
4.1 Global Machine Learning Tools Historic Market Size by Type (2019-2024)
4.2 Global Machine Learning Tools Forecasted Market Size by Type (2025-2030)
5 Machine Learning Tools Breakdown Data by Application
5.1 Global Machine Learning Tools Historic Market Size by Application (2019-2024)
5.2 Global Machine Learning Tools Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Machine Learning Tools Market Size (2019-2030)
6.2 North America Machine Learning Tools Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America Machine Learning Tools Market Size by Country (2019-2024)
6.4 North America Machine Learning Tools Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Machine Learning Tools Market Size (2019-2030)
7.2 Europe Machine Learning Tools Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe Machine Learning Tools Market Size by Country (2019-2024)
7.4 Europe Machine Learning Tools Market Size by Country (2025-2030)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Machine Learning Tools Market Size (2019-2030)
8.2 Asia-Pacific Machine Learning Tools Market Growth Rate by Region: 2019 VS 2023 VS 2030
8.3 Asia-Pacific Machine Learning Tools Market Size by Region (2019-2024)
8.4 Asia-Pacific Machine Learning Tools Market Size by Region (2025-2030)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Machine Learning Tools Market Size (2019-2030)
9.2 Latin America Machine Learning Tools Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America Machine Learning Tools Market Size by Country (2019-2024)
9.4 Latin America Machine Learning Tools Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Machine Learning Tools Market Size (2019-2030)
10.2 Middle East & Africa Machine Learning Tools Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa Machine Learning Tools Market Size by Country (2019-2024)
10.4 Middle East & Africa Machine Learning Tools Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Microsoft
11.1.1 Microsoft Company Detail
11.1.2 Microsoft Business Overview
11.1.3 Microsoft Machine Learning Tools Introduction
11.1.4 Microsoft Revenue in Machine Learning Tools Business (2019-2024)
11.1.5 Microsoft Recent Development
11.2 IBM
11.2.1 IBM Company Detail
11.2.2 IBM Business Overview
11.2.3 IBM Machine Learning Tools Introduction
11.2.4 IBM Revenue in Machine Learning Tools Business (2019-2024)
11.2.5 IBM Recent Development
11.3 Google
11.3.1 Google Company Detail
11.3.2 Google Business Overview
11.3.3 Google Machine Learning Tools Introduction
11.3.4 Google Revenue in Machine Learning Tools Business (2019-2024)
11.3.5 Google Recent Development
11.4 RStudio
11.4.1 RStudio Company Detail
11.4.2 RStudio Business Overview
11.4.3 RStudio Machine Learning Tools Introduction
11.4.4 RStudio Revenue in Machine Learning Tools Business (2019-2024)
11.4.5 RStudio Recent Development
11.5 Amazon
11.5.1 Amazon Company Detail
11.5.2 Amazon Business Overview
11.5.3 Amazon Machine Learning Tools Introduction
11.5.4 Amazon Revenue in Machine Learning Tools Business (2019-2024)
11.5.5 Amazon Recent Development
11.6 Oracle
11.6.1 Oracle Company Detail
11.6.2 Oracle Business Overview
11.6.3 Oracle Machine Learning Tools Introduction
11.6.4 Oracle Revenue in Machine Learning Tools Business (2019-2024)
11.6.5 Oracle Recent Development
11.7 Meta Platforms
11.7.1 Meta Platforms Company Detail
11.7.2 Meta Platforms Business Overview
11.7.3 Meta Platforms Machine Learning Tools Introduction
11.7.4 Meta Platforms Revenue in Machine Learning Tools Business (2019-2024)
11.7.5 Meta Platforms Recent Development
11.8 Kira
11.8.1 Kira Company Detail
11.8.2 Kira Business Overview
11.8.3 Kira Machine Learning Tools Introduction
11.8.4 Kira Revenue in Machine Learning Tools Business (2019-2024)
11.8.5 Kira Recent Development
11.9 Databricks
11.9.1 Databricks Company Detail
11.9.2 Databricks Business Overview
11.9.3 Databricks Machine Learning Tools Introduction
11.9.4 Databricks Revenue in Machine Learning Tools Business (2019-2024)
11.9.5 Databricks Recent Development
11.10 DataRobot
11.10.1 DataRobot Company Detail
11.10.2 DataRobot Business Overview
11.10.3 DataRobot Machine Learning Tools Introduction
11.10.4 DataRobot Revenue in Machine Learning Tools Business (2019-2024)
11.10.5 DataRobot Recent Development
11.11 OpenText
11.11.1 OpenText Company Detail
11.11.2 OpenText Business Overview
11.11.3 OpenText Machine Learning Tools Introduction
11.11.4 OpenText Revenue in Machine Learning Tools Business (2019-2024)
11.11.5 OpenText Recent Development
11.12 Scikit-learn
11.12.1 Scikit-learn Company Detail
11.12.2 Scikit-learn Business Overview
11.12.3 Scikit-learn Machine Learning Tools Introduction
11.12.4 Scikit-learn Revenue in Machine Learning Tools Business (2019-2024)
11.12.5 Scikit-learn Recent Development
11.13 Catalyst
11.13.1 Catalyst Company Detail
11.13.2 Catalyst Business Overview
11.13.3 Catalyst Machine Learning Tools Introduction
11.13.4 Catalyst Revenue in Machine Learning Tools Business (2019-2024)
11.13.5 Catalyst Recent Development
11.14 XGBoost
11.14.1 XGBoost Company Detail
11.14.2 XGBoost Business Overview
11.14.3 XGBoost Machine Learning Tools Introduction
11.14.4 XGBoost Revenue in Machine Learning Tools Business (2019-2024)
11.14.5 XGBoost Recent Development
11.15 LightGBM
11.15.1 LightGBM Company Detail
11.15.2 LightGBM Business Overview
11.15.3 LightGBM Machine Learning Tools Introduction
11.15.4 LightGBM Revenue in Machine Learning Tools Business (2019-2024)
11.15.5 LightGBM Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
Microsoft
IBM
Google
RStudio
Amazon
Oracle
Meta Platforms
Kira
Databricks
DataRobot
OpenText
Scikit-learn
Catalyst
XGBoost
LightGBM
听
听
*If Applicable.
