查看购物车
  • Traditional Chinese
  • English
  • Japanese
封面
市场调查报告书
商品编码
1711070

2025年无代码机器学习全球市场报告

No-Code Machine Learning Global Market Report 2025
出版日期: | 出版商: The Business Research Company | 英文 200 Pages | 商品交期: 2-10个工作天内

价格
简介目录

预计未来几年无程式码机器学习市场规模将呈指数级增长。到 2029 年，这一数字将成长至 42.1 亿美元，复合年增长率为 30.6%。预测期内的成长可以归因于对可访问 AI 工具的需求增长、各个行业对 AI 的采用增加、预建机器学习模板的可用性增加以及对降低技术技能障碍的日益关注。预测期内的关键趋势包括技术进步、人工智慧主导的个人化、物联网应用、预测分析和自助服务分析。

物联网 (IoT) 的日益普及预计将推动无程式码机器学习市场的未来成长。物联网 (IoT) 是指透过网际网路通讯和交换资料以实现流程自动化和提高业务效率的互连设备和系统网路。物联网的采用源于其连接和优化各种设备和系统的能力，以提高业务效率、提供即时数据洞察、实现自动化和远端监控、降低成本、改善决策并推动各个行业的创新。无程式码机器学习在物联网生态系统中得到越来越广泛的应用，它简化了机器学习模型的创建、部署和管理，而无需大量的技术专业知识。例如，2022 年 11 月，瑞典网路和通讯公司爱立信预测，全球物联网连接设备的数量将从 2022 年的 132 亿增加到 2028 年的 347 亿。因此，物联网的普及正在推动无程式码机器学习市场的扩张。

无程式码机器学习市场的主要企业正专注于开发无程式码机器学习工具等先进技术，以增强工作流程自动化。这些工具使用户无需说明程式码即可创建和部署机器学习模型，从而使没有技术专业知识的用户更容易使用该技术。例如，2023年12月，美国科技公司亚马逊宣布推出SageMaker Canvas，这是一款针对没有程式设计经验的用户的无程式码机器学习工具。该工具专为业务分析师和非技术用户设计，提供用户友好的介面，方便创建模型、准备数据和训练。 SageMaker Canvas 的主要应用包括客户流失预测、诈欺侦测和库存优化。

目录

第一章执行摘要

第二章 市场特征

第三章 市场趋势与策略

第四章 市场 - 宏观经济情景，包括利率、感染疾病、地缘政治、新冠疫情、经济復苏对市场的影响

第五章 全球成长分析与策略分析框架

  • 全球无程式码机器学习 PESTEL 分析（政治、社会、技术、环境、法律因素、驱动因素和限制因素）
  • 最终用途产业分析
  • 全球无程式码机器学习市场：成长率分析
  • 全球无程式码机器学习市场表现：规模与成长，2019-2024
  • 全球无程式码机器学习市场预测：规模与成长，2024-2029 年，2034 年
  • 全球无程式码机器学习总目标市场（TAM）

第六章市场区隔

  • 全球无程式码机器学习市场：按产品、效能和预测，2019-2024 年、2024-2029 年、2034 年
  • 平台
  • 服务
  • 全球无程式码机器学习市场（按部署模式、效能和预测），2019-2024 年、2024-2029 年、2034 年
  • 云端基础
  • 本地
  • 全球无程式码机器学习市场：依产业、绩效及预测，2019-2024 年、2024-2029 年、2034 年
  • 银行、金融服务和保险（BFSI）
  • 卫生保健
  • 零售
  • 资讯科技（IT）和通讯
  • 製造业
  • 政府
  • 全球无程式码机器学习市场：按应用、效能和预测，2019-2024 年、2024-2029 年、2034 年
  • 预测分析
  • 流程自动化
  • 数据视觉化
  • 商业智慧
  • 客户关係管理
  • 供应链优化
  • 全球无程式码机器学习市场平台细分（按类型）、绩效及预测，2019-2024 年、2024-2029 年、2034 年
  • 自动化机器学习平台（AutoML）
  • 拖放式机器学习平台
  • 模型部署平台
  • 资料准备平台
  • 可视化和报告平台
  • API和资料源整合平台
  • 全球无程式码机器学习市场，按服务类型、效能和预测细分，2019-2024 年、2024-2029 年、2034 年
  • 咨询服务
  • 实施服务
  • 培训和教育服务
  • 支援和维护服务
  • 客自订解决方案开发服务

第七章 区域和国家分析

  • 全球无程式码机器学习市场：按地区、绩效及预测，2019-2024 年、2024-2029 年、2034 年
  • 全球无程式码机器学习市场：按国家、表现和预测，2019-2024 年、2024-2029 年、2034 年

第八章 亚太市场

第九章：中国市场

第十章 印度市场

第十一章 日本市场

第十二章 澳洲市场

第十三章 印尼市场

第十四章 韩国市场

第十五章 西欧市场

第十六章英国市场

第十七章 德国市场

第十八章 法国市场

第十九章：义大利市场

第20章：西班牙市场

第21章 东欧市场

第22章 俄罗斯市场

第23章 北美市场

第24章美国市场

第25章：加拿大市场

第26章 南美洲市场

第27章：巴西市场

第28章 中东市场

第29章：非洲市场

第30章竞争格局与公司概况

  • 无程式码机器学习市场：竞争格局
  • 无程式码机器学习市场：公司简介
    • Apple Create ML Overview, Products and Services, Strategy and Financial Analysis
    • Microsoft Azure Machine Learning Studio Overview, Products and Services, Strategy and Financial Analysis
    • Amazon Web Services Overview, Products and Services, Strategy and Financial Analysis
    • SAS Viya Overview, Products and Services, Strategy and Financial Analysis
    • DataRobot Inc. Overview, Products and Services, Strategy and Financial Analysis

第31章 其他大型创新企业

  • LityxIQ
  • H2O.ai
  • Dataiku DSS
  • C3 AI Suite
  • RapidMiner Studio
  • BigML Inc.
  • Google Teachable Machine
  • Edge Impulse
  • Microsoft Lobe
  • KNIME Analytics Platform
  • MonkeyLearn
  • Akkio AI
  • Obviously AI
  • Runway ML
  • Fritz AI

第 32 章全球市场竞争基准化分析与仪表板

第33章 重大併购

第34章近期市场趋势

第 35 章 高市场潜力国家、细分市场与策略

  • 2029 年无程式码机器学习市场：提供新机会的国家
  • 2029 年无程式码机器学习市场：细分领域带来新机会
  • 2029 年无程式码机器学习市场：成长策略
    • 基于市场趋势的策略
    • 竞争对手的策略

第36章 附录

简介目录
Product Code: r32095

No-code machine learning refers to the practice of developing, deploying, and managing machine learning models without writing any code. This approach typically involves using graphical interfaces, drag-and-drop tools, and pre-built templates provided by no-code platforms. These platforms abstract the complexities of programming and data science, enabling users, often non-technical professionals, to build and use machine learning models by following intuitive steps.

The main offering of no-code machine learning offerings include platforms and services. A no-code machine learning platform is a software tool that enables users to create, train, and deploy machine learning models without writing any code, using a visual interface to simplify the process for non-technical users. It can be deployed both on the cloud and on-premise and is used by various industries such as banking, financial services and insurance (BFSI), healthcare, retail, information technology (IT), telecom, manufacturing, and government. It is used for various applications, including predictive analytics, process automation, data visualization, business intelligence, customer relationship management, and supply chain optimization.

The no-code machine learning market research report is one of a series of new reports from The Business Research Company that provides no-code machine learning market statistics, including no-code machine learning industry global market size, regional shares, competitors with a no-code machine learning market share, detailed no-code machine learning market segments, market trends and opportunities, and any further data you may need to thrive in the no-code machine learning industry. This no-code machine learning market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The no-code machine learning market size has grown exponentially in recent years. It will grow from $1.1 $ billion in 2024 to $1.45 $ billion in 2025 at a compound annual growth rate (CAGR) of 31.0%. The growth in the historic period can be attributed to increasing demand for user-friendly tools, rise in need for cost-effective machine learning solutions, increasing use of cloud-based no-code platforms, increasing awareness of machine learning benefits among non-technical users, and rise in popularity of low-code and no-code platforms.

The no-code machine learning market size is expected to see exponential growth in the next few years. It will grow to $4.21 $ billion in 2029 at a compound annual growth rate (CAGR) of 30.6%. The growth in the forecast period can be attributed to rising demand for accessible AI tools, rising adoption of AI across various sectors, growing adoption of cloud computing, increasing availability of pre-built machine learning templates, and growing focus on reducing the technical skills barrier. Major trends in the forecast period include technological advancements, AI-driven personalization, IoT applications, predictive analytics, and self-service analytics.

The increasing adoption of the Internet of Things (IoT) is expected to drive growth in the no-code machine learning market in the future. The Internet of Things (IoT) refers to a network of interconnected devices and systems that communicate and exchange data over the Internet to automate processes and improve operational efficiency. The adoption of IoT is driven by its ability to enhance operational efficiency, provide real-time data insights, enable automation and remote monitoring, reduce costs, improve decision-making, and foster innovation across various industries by connecting and optimizing a broad range of devices and systems. No-code machine learning is increasingly utilized within the IoT ecosystem to simplify the creation, deployment, and management of machine learning models without requiring extensive technical expertise. For example, in November 2022, Ericsson, a Sweden-based network and telecommunications company, projected that the number of global IoT-connected devices would grow from 13.2 billion in 2022 to 34.7 billion by 2028. Consequently, the rise in IoT adoption is fueling the expansion of the no-code machine learning market.

Major companies in the no-code machine learning market are focusing on developing advanced technologies to enhance workflow automation, including no-code machine learning tools. These tools enable users to create and deploy machine learning models without writing any code, making the technology more accessible to those without technical expertise. For example, in December 2023, Amazon, a US-based technology company, introduced SageMaker Canvas, a no-code machine learning tool aimed at users without coding experience. This tool is designed for business analysts and non-technical users, offering a user-friendly interface for easy model creation, data preparation, and training. Key applications of SageMaker Canvas include customer churn prediction, fraud detection, and inventory optimization.

In July 2024, Forwrd.ai, a US-based data science automation platform, acquired LoudnClear.ai for an undisclosed amount. This acquisition will enable LoudnClear.ai to further its mission of helping revenue operations and business teams swiftly analyze unstructured data and gain insights into customer sentiment through NLP, machine learning, and AI. LoudnClear.ai, based in Israel, specializes in providing no-code machine learning solutions.

Major companies operating in the no-code machine learning market are Apple Create ML, Microsoft Azure Machine Learning Studio, Amazon Web Services, SAS Viya, DataRobot Inc, LityxIQ, H2O.ai, Dataiku DSS, C3 AI Suite, RapidMiner Studio, BigML Inc., Google Teachable Machine, Edge Impulse, Microsoft Lobe, KNIME Analytics Platform, MonkeyLearn, Akkio AI, Obviously AI, Runway ML, Fritz AI, Sway AI, PyCaret, Ever AI, Neural Designer

North America was the largest region in the no-code machine learning market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the no-code machine learning market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the no-code machine learning market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The no-code machine learning market consists of revenues earned by entities by providing services such as model building, data preparation, data visualization, model training and evaluation. The market value includes the value of related goods sold by the service provider or included within the service offering. The no-code machine learning market also includes sales of data preparation tools, automated machine learning solutions, drag-and-drop workflow builders and predictive analytics tools. Values in this market are 'factory gate' values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

No-Code Machine Learning Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on no-code machine learning market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

Reasons to Purchase

  • Gain a truly global perspective with the most comprehensive report available on this market covering 15 geographies.
  • Assess the impact of key macro factors such as conflict, pandemic and recovery, inflation and interest rate environment and the 2nd Trump presidency.
  • Create regional and country strategies on the basis of local data and analysis.
  • Identify growth segments for investment.
  • Outperform competitors using forecast data and the drivers and trends shaping the market.
  • Understand customers based on the latest market shares.
  • Benchmark performance against key competitors.
  • Suitable for supporting your internal and external presentations with reliable high quality data and analysis
  • Report will be updated with the latest data and delivered to you within 2-3 working days of order along with an Excel data sheet for easy data extraction and analysis.
  • All data from the report will also be delivered in an excel dashboard format.

Where is the largest and fastest growing market for no-code machine learning ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The no-code machine learning market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

  • The market characteristics section of the report defines and explains the market.
  • The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
  • The forecasts are made after considering the major factors currently impacting the market. These include:

The forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.

  • Market segmentations break down the market into sub markets.
  • The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth. It covers the growth trajectory of COVID-19 for all regions, key developed countries and major emerging markets.
  • The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
  • The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.

Scope

  • Markets Covered:1) By Offering: Platform; Services
  • 2) By Deployment Mode: Cloud-Based; On-Premise
  • 3) By Industry Vertical: Banking, Financial Services And Insurance (BFSI); Healthcare; Retail; Information Technology(IT) And Telecom; Manufacturing; Government
  • 4) By Application: Predictive Analytics; Process Automation; Data Visualization; Business Intelligence; Customer Relationship Management; Supply Chain Optimization
  • Subsegments:
  • 1) By Platform: Automated Machine Learning Platforms (AutoML); Drag-and-Drop Machine Learning Platforms; Model Deployment Platforms; Data Preparation Platforms; Visualization Aand Reporting Platforms; Integration Platforms for APIs And Data Sources
  • 2) By Services: Consulting Services; Implementation Services; Training and Education Services; Support And Maintenance Services; Custom Solution Development Services
  • Companies Mentioned: Apple Create ML; Microsoft Azure Machine Learning Studio; Amazon Web Services; SAS Viya; DataRobot Inc
  • Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain
  • Regions: Asia-Pacific; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
  • Time series: Five years historic and ten years forecast.
  • Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
  • Data segmentations: country and regional historic and forecast data, market share of competitors, market segments.
  • Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
  • Delivery format: PDF, Word and Excel Data Dashboard.

Table of Contents

1. Executive Summary

2. No-Code Machine Learning Market Characteristics

3. No-Code Machine Learning Market Trends And Strategies

4. No-Code Machine Learning Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Covid And Recovery On The Market

5. Global No-Code Machine Learning Growth Analysis And Strategic Analysis Framework

  • 5.1. Global No-Code Machine Learning PESTEL Analysis (Political, Social, Technological, Environmental and Legal Factors, Drivers and Restraints)
  • 5.2. Analysis Of End Use Industries
  • 5.3. Global No-Code Machine Learning Market Growth Rate Analysis
  • 5.4. Global No-Code Machine Learning Historic Market Size and Growth, 2019 - 2024, Value ($ Billion)
  • 5.5. Global No-Code Machine Learning Forecast Market Size and Growth, 2024 - 2029, 2034F, Value ($ Billion)
  • 5.6. Global No-Code Machine Learning Total Addressable Market (TAM)

6. No-Code Machine Learning Market Segmentation

  • 6.1. Global No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Platform
  • Services
  • 6.2. Global No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Cloud-Based
  • On-Premise
  • 6.3. Global No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Banking, Financial Services And Insurance (BFSI)
  • Healthcare
  • Retail
  • Information Technology (IT) And Telecom
  • Manufacturing
  • Government
  • 6.4. Global No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Predictive Analytics
  • Process Automation
  • Data Visualization
  • Business Intelligence
  • Customer Relationship Management
  • Supply Chain Optimization
  • 6.5. Global No-Code Machine Learning Market, Sub-Segmentation Of Platform, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Automated Machine Learning Platforms (AutoML)
  • Drag-and-Drop Machine Learning Platforms
  • Model Deployment Platforms
  • Data Preparation Platforms
  • Visualization And Reporting Platforms
  • Integration Platforms for APIs And Data Sources
  • 6.6. Global No-Code Machine Learning Market, Sub-Segmentation Of Services, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • Consulting Services
  • Implementation Services
  • Training and Education Services
  • Support And Maintenance Services
  • Custom Solution Development Services

7. No-Code Machine Learning Market Regional And Country Analysis

  • 7.1. Global No-Code Machine Learning Market, Split By Region, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 7.2. Global No-Code Machine Learning Market, Split By Country, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

8. Asia-Pacific No-Code Machine Learning Market

  • 8.1. Asia-Pacific No-Code Machine Learning Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 8.2. Asia-Pacific No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 8.3. Asia-Pacific No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 8.4. Asia-Pacific No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

9. China No-Code Machine Learning Market

  • 9.1. China No-Code Machine Learning Market Overview
  • 9.2. China No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion
  • 9.3. China No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion
  • 9.4. China No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion

10. India No-Code Machine Learning Market

  • 10.1. India No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 10.2. India No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 10.3. India No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

11. Japan No-Code Machine Learning Market

  • 11.1. Japan No-Code Machine Learning Market Overview
  • 11.2. Japan No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 11.3. Japan No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 11.4. Japan No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

12. Australia No-Code Machine Learning Market

  • 12.1. Australia No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 12.2. Australia No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 12.3. Australia No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

13. Indonesia No-Code Machine Learning Market

  • 13.1. Indonesia No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 13.2. Indonesia No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 13.3. Indonesia No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

14. South Korea No-Code Machine Learning Market

  • 14.1. South Korea No-Code Machine Learning Market Overview
  • 14.2. South Korea No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 14.3. South Korea No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 14.4. South Korea No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

15. Western Europe No-Code Machine Learning Market

  • 15.1. Western Europe No-Code Machine Learning Market Overview
  • 15.2. Western Europe No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 15.3. Western Europe No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 15.4. Western Europe No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

16. UK No-Code Machine Learning Market

  • 16.1. UK No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 16.2. UK No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 16.3. UK No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

17. Germany No-Code Machine Learning Market

  • 17.1. Germany No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 17.2. Germany No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 17.3. Germany No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

18. France No-Code Machine Learning Market

  • 18.1. France No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 18.2. France No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 18.3. France No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

19. Italy No-Code Machine Learning Market

  • 19.1. Italy No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 19.2. Italy No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 19.3. Italy No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

20. Spain No-Code Machine Learning Market

  • 20.1. Spain No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 20.2. Spain No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 20.3. Spain No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

21. Eastern Europe No-Code Machine Learning Market

  • 21.1. Eastern Europe No-Code Machine Learning Market Overview
  • 21.2. Eastern Europe No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 21.3. Eastern Europe No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 21.4. Eastern Europe No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

22. Russia No-Code Machine Learning Market

  • 22.1. Russia No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 22.2. Russia No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 22.3. Russia No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

23. North America No-Code Machine Learning Market

  • 23.1. North America No-Code Machine Learning Market Overview
  • 23.2. North America No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 23.3. North America No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 23.4. North America No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

24. USA No-Code Machine Learning Market

  • 24.1. USA No-Code Machine Learning Market Overview
  • 24.2. USA No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 24.3. USA No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 24.4. USA No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

25. Canada No-Code Machine Learning Market

  • 25.1. Canada No-Code Machine Learning Market Overview
  • 25.2. Canada No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 25.3. Canada No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 25.4. Canada No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

26. South America No-Code Machine Learning Market

  • 26.1. South America No-Code Machine Learning Market Overview
  • 26.2. South America No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 26.3. South America No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 26.4. South America No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

27. Brazil No-Code Machine Learning Market

  • 27.1. Brazil No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 27.2. Brazil No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 27.3. Brazil No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

28. Middle East No-Code Machine Learning Market

  • 28.1. Middle East No-Code Machine Learning Market Overview
  • 28.2. Middle East No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 28.3. Middle East No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 28.4. Middle East No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

29. Africa No-Code Machine Learning Market

  • 29.1. Africa No-Code Machine Learning Market Overview
  • 29.2. Africa No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 29.3. Africa No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
  • 29.4. Africa No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

30. No-Code Machine Learning Market Competitive Landscape And Company Profiles

  • 30.1. No-Code Machine Learning Market Competitive Landscape
  • 30.2. No-Code Machine Learning Market Company Profiles
    • 30.2.1. Apple Create ML Overview, Products and Services, Strategy and Financial Analysis
    • 30.2.2. Microsoft Azure Machine Learning Studio Overview, Products and Services, Strategy and Financial Analysis
    • 30.2.3. Amazon Web Services Overview, Products and Services, Strategy and Financial Analysis
    • 30.2.4. SAS Viya Overview, Products and Services, Strategy and Financial Analysis
    • 30.2.5. DataRobot Inc. Overview, Products and Services, Strategy and Financial Analysis

31. No-Code Machine Learning Market Other Major And Innovative Companies

  • 31.1. LityxIQ
  • 31.2. H2O.ai
  • 31.3. Dataiku DSS
  • 31.4. C3 AI Suite
  • 31.5. RapidMiner Studio
  • 31.6. BigML Inc.
  • 31.7. Google Teachable Machine
  • 31.8. Edge Impulse
  • 31.9. Microsoft Lobe
  • 31.10. KNIME Analytics Platform
  • 31.11. MonkeyLearn
  • 31.12. Akkio AI
  • 31.13. Obviously AI
  • 31.14. Runway ML
  • 31.15. Fritz AI

32. Global No-Code Machine Learning Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The No-Code Machine Learning Market

34. Recent Developments In The No-Code Machine Learning Market

35. No-Code Machine Learning Market High Potential Countries, Segments and Strategies

  • 35.1 No-Code Machine Learning Market In 2029 - Countries Offering Most New Opportunities
  • 35.2 No-Code Machine Learning Market In 2029 - Segments Offering Most New Opportunities
  • 35.3 No-Code Machine Learning Market In 2029 - Growth Strategies
    • 35.3.1 Market Trend Based Strategies
    • 35.3.2 Competitor Strategies

36. Appendix

  • 36.1. Abbreviations
  • 36.2. Currencies
  • 36.3. Historic And Forecast Inflation Rates
  • 36.4. Research Inquiries
  • 36.5. The Business Research Company
  • 36.6. Copyright And Disclaimer