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市場調查報告書
商品編碼
1711070

2025年無代碼機器學習全球市場報告

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個工作天內

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簡介目錄

預計未來幾年無程式碼機器學習市場規模將呈指數級成長。到 2029 年，這一數字將成長至 42.1 億美元，複合年成長率為 30.6%。預測期內的成長可以歸因於對可訪問 AI 工具的需求成長、各個行業對 AI 的採用增加、預建機器學習模板的可用性增加以及對降低技術技能障礙的日益關注。預測期內的關鍵趨勢包括技術進步、人工智慧主導的個人化、物聯網應用、預測分析和自助服務分析。

物聯網 (IoT) 的日益普及預計將推動無程式碼機器學習市場的未來成長。物聯網 (IoT) 是指透過網際網路通訊和交換資料以實現流程自動化和提高業務效率的互連設備和系統網路。物聯網的採用源於其連接和最佳化各種設備和系統的能力，以提高業務效率、提供即時數據洞察、實現自動化和遠端監控、降低成本、改善決策並推動各個行業的創新。無程式碼機器學習在物聯網生態系統中得到越來越廣泛的應用，它簡化了機器學習模型的創建、部署和管理，而無需大量的技術專業知識。例如，2022 年 11 月，瑞典網路和通訊公司愛立信預測，全球物聯網連接設備的數量將從 2022 年的 132 億增加到 2028 年的 347 億。因此，物聯網的普及正在推動無程式碼機器學習市場的擴張。

無程式碼機器學習市場的主要企業正專注於開發無程式碼機器學習工具等先進技術，以增強工作流程自動化。這些工具使用戶無需說明程式碼即可創建和部署機器學習模型，從而使沒有技術專業知識的用戶更容易使用該技術。例如，2023年12月，美國科技公司亞馬遜宣布推出SageMaker Canvas，這是一款針對沒有程式設計經驗的用戶的無程式碼機器學習工具。該工具專為業務分析師和非技術用戶設計，提供方便用戶使用的介面，方便創建模型、準備數據和訓練。 SageMaker Canvas 的主要應用包括客戶流失預測、詐欺偵測和庫存最佳化。

目錄

第1章執行摘要

第2章 市場特徵

第3章 市場趨勢與策略

第4章 市場 - 宏觀經濟情景，包括利率、感染疾病、地緣政治、新冠疫情、經濟復甦對市場的影響

第5章 全球成長分析與策略分析框架

  • 全球無程式碼機器學習 PESTEL 分析（政治、社會、技術、環境、法律因素、促進因素和限制因素）
  • 最終用途產業分析
  • 全球無程式碼機器學習市場：成長率分析
  • 全球無程式碼機器學習市場表現：規模與成長，2019-2024
  • 全球無程式碼機器學習市場預測：規模與成長，2024-2029 年，2034 年
  • 全球無程式碼機器學習總目標市場（TAM）

第6章市場區隔

  • 全球無程式碼機器學習市場：按產品、效能和預測，2019-2024 年、2024-2029 年、2034 年
  • 平台
  • 服務
  • 全球無程式碼機器學習市場（按部署模式、效能和預測），2019-2024 年、2024-2029 年、2034 年
  • 雲端基礎
  • 本地
  • 全球無程式碼機器學習市場：依產業、績效及預測，2019-2024 年、2024-2029 年、2034 年
  • 銀行、金融服務和保險（BFSI）
  • 衛生保健
  • 零售
  • 資訊科技（IT）和通訊
  • 製造業
  • 政府
  • 全球無程式碼機器學習市場：按應用、效能和預測，2019-2024 年、2024-2029 年、2034 年
  • 預測分析
  • 流程自動化
  • 數據視覺化
  • 商業智慧
  • 客戶關係管理
  • 供應鏈最佳化
  • 全球無程式碼機器學習市場平台細分（按類型）、績效及預測，2019-2024 年、2024-2029 年、2034 年
  • 自動化機器學習平台（AutoML）
  • 拖放式機器學習平台
  • 模型部署平台
  • 資料準備平台
  • 可視化和報告平台
  • API和資料源整合平台
  • 全球無程式碼機器學習市場，按服務類型、效能和預測細分，2019-2024 年、2024-2029 年、2034 年
  • 諮詢服務
  • 實施服務
  • 培訓和教育服務
  • 支援和維護服務
  • 客自訂解決方案開發服務

第7章 區域和國家分析

  • 全球無程式碼機器學習市場：按地區、績效及預測，2019-2024 年、2024-2029 年、2034 年
  • 全球無程式碼機器學習市場：按國家、表現和預測，2019-2024 年、2024-2029 年、2034 年

第8章 亞太市場

第9章：中國市場

第10章 印度市場

第11章 日本市場

第12章 澳洲市場

第13章 印尼市場

第14章 韓國市場

第15章 西歐市場

第16章英國市場

第17章 德國市場

第18章 法國市場

第19章：義大利市場

第20章：西班牙市場

第21章 東歐市場

第22章 俄羅斯市場

第23章 北美市場

第24章美國市場

第25章：加拿大市場

第26章 南美洲市場

第27章：巴西市場

第28章 中東市場

第29章：非洲市場

第30章競爭格局與公司概況

  • 無程式碼機器學習市場：競爭格局
  • 無程式碼機器學習市場：公司簡介
    • 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 其他大型創新企業

  • 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 章全球市場競爭基準化分析與儀表板

第33章 重大併購

第34章近期市場趨勢

第 35 章 高市場潛力國家、細分市場與策略

  • 2029 年無程式碼機器學習市場：提供新機會的國家
  • 2029 年無程式碼機器學習市場：細分領域帶來新機會
  • 2029 年無程式碼機器學習市場：成長策略
    • 基於市場趨勢的策略
    • 競爭對手的策略

第36章 附錄

簡介目錄
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.

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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