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市場調查報告書
商品編碼
1619783

2024 年無程式碼機器學習全球市場報告

No-Code Machine Learning Global Market Report 2024
出版日期: | 出版商: The Business Research Company | 英文 175 Pages | 商品交期: 2-10個工作天內

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簡介目錄

無程式碼機器學習市場規模預計在未來幾年將呈指數級成長。 2028年，將以30.7%的複合年成長率成長至32.2億美元。預測期內的成長是由於對易於使用的人工智慧工具的需求增加、人工智慧在各個領域的廣泛採用、雲端運算的使用不斷增加、預先建構機器學習模板和技術的可用性不斷擴大而推動的。降低技能壁壘。這段時期的主要趨勢包括技術進步、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) 是指由互連設備和系統組成的網路，透過網際網路通訊和交換資料，以實現流程自動化並提高業務效率。採用物聯網可以透過連接和最佳化各種設備和系統來提高業務效率，提供即時資料洞察，實現自動化和遠端監控，降低成本並改善決策，這得益於其促進創新的能力。無程式碼機器學習在物聯網生態系統中得到越來越多的利用，以簡化機器學習模型的創建、部署和管理，而無需廣泛的技術專業知識。例如，總部位於瑞典的網路和通訊公司愛立信在2022年11月預測，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，物聯網採用的不斷增加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專注於開發先進技術以增強工作流程自動化，例如無程式碼機器學習工具。這些工具允許使用者在不說明任何程式碼的情況下創建和部署機器學習模型，從而使沒有技術專業知識的使用者更容易使用該技術。例如，2023年12月，美國科技公司亞馬遜發表了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，可輕鬆創建模型、資料準備和培訓。 SageMaker Canvas 的主要用途包括預測客戶流失、偵測詐欺和最佳化庫存。

目錄

第1章執行摘要

第2章 市場特點

第3章 市場趨勢與策略

第4章宏觀經濟情景

  • 高通膨對市場的影響
  • 烏克蘭與俄羅斯戰爭對市場的影響
  • COVID-19 對市場的影響

第5章世界市場規模與成長

  • 全球無程式碼機器學習市場：促進因素與限制
    • 市場促進因素
    • 市場限制因素
  • 全球無程式碼機器學習市場表現：規模與成長，2018-2023 年
  • 全球無程式碼機器學習市場預測：規模與成長，2023-2028 年、2033 年

第6章 市場細分

  • 全球無程式碼機器學習市場：依產品、實際及預測分類，2018-2023、2023-2028、2033
  • 平台
  • 服務
  • 全球無程式碼機器學習市場：依部署模式分類的效能與預測，2018-2023、2023-2028、2033
  • 雲端基礎
  • 本地
  • 全球無程式碼機器學習市場：按產業、實際和預測，2018-2023、2023-2028、2033
  • 銀行、金融服務和保險 (BFSI)
  • 醫療保健
  • 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、實際和預測分類，2018-2023、2023-2028、2033
  • 預測分析
  • 流程自動化
  • 資料視覺化
  • 商業智慧
  • 客戶關係管理
  • 供應鏈最佳化

第 7 章 區域/國家分析

  • 全球無程式碼機器學習市場：按地區、表現和預測，2018-2023、2023-2028、2033
  • 全球無程式碼機器學習市場：按國家、績效和預測，2018-2023、2023-2028、2033

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 競爭格局及公司概況

  • 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
    • Microsoft Azure Machine Learning Studio
    • Amazon Web Services
    • SAS Viya
    • DataRobot Inc

第31章 其他重大及創新企業

  • 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章競爭基準化分析

第 33 章. 競爭對手儀表板

第34章 重大併購

第35章 未來展望與潛力分析

第36章附錄

簡介目錄
Product Code: r20770

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 $0.85 billion in 2023 to $1.10 billion in 2024 at a compound annual growth rate (CAGR) of 30.3%. The growth during the historic period can be attributed to a rising demand for user-friendly tools, an increasing need for cost-effective machine learning solutions, greater use of cloud-based no-code platforms, heightened awareness of machine learning benefits among non-technical users, and the growing 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 $3.22 billion in 2028 at a compound annual growth rate (CAGR) of 30.7%. The growth during the forecast period can be attributed to the increasing demand for accessible AI tools, broader adoption of AI across different sectors, growing use of cloud computing, greater availability of pre-built machine learning templates, and a focus on lowering the barrier to technical skills. Key trends expected in this 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 2024 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 50+ geographies.
  • Understand how the market has been affected by the COVID-19 and how it is responding as the impact of the virus abates.
  • Assess the Russia - Ukraine war's impact on agriculture, energy and mineral commodity supply and its direct and indirect impact on the market.
  • Measure the impact of high global inflation on market growth.
  • 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 3-5 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 impact of sanctions, supply chain disruptions, and altered demand for goods and services due to the Russian Ukraine war, impacting various macro-economic factors and parameters in the Eastern European region and its subsequent effect on global markets.

The impact of higher inflation in many countries and the resulting spike in interest rates.

The continued but declining impact of COVID-19 on supply chains and consumption patterns.

  • 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
  • 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

  • 4.1. Impact Of High Inflation On The Market
  • 4.2. Ukraine-Russia War Impact On The Market
  • 4.3. COVID-19 Impact On The Market

5. Global No-Code Machine Learning Market Size and Growth

  • 5.1. Global No-Code Machine Learning Market Drivers and Restraints
    • 5.1.1. Drivers Of The Market
    • 5.1.2. Restraints Of The Market
  • 5.2. Global No-Code Machine Learning Historic Market Size and Growth, 2018 - 2023, Value ($ Billion)
  • 5.3. Global No-Code Machine Learning Forecast Market Size and Growth, 2023 - 2028, 2033F, Value ($ Billion)

6. No-Code Machine Learning Market Segmentation

  • 6.1. Global No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • Platform
  • Services
  • 6.2. Global No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • Cloud-Based
  • On-Premise
  • 6.3. Global No-Code Machine Learning Market, Segmentation By Industry Vertical, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • Predictive Analytics
  • Process Automation
  • Data Visualization
  • Business Intelligence
  • Customer Relationship Management
  • Supply Chain Optimization

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

  • 7.1. Global No-Code Machine Learning Market, Split By Region, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 7.2. Global No-Code Machine Learning Market, Split By Country, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

8. Asia-Pacific No-Code Machine Learning Market

  • 8.1. Asia-Pacific No-Code Machine Learning Market Overview
  • Region Information, Impact Of COVID-19, 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 8.3. Asia-Pacific No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 8.4. Asia-Pacific No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F,$ Billion
  • 9.3. China No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F,$ Billion
  • 9.4. China No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F,$ Billion

10. India No-Code Machine Learning Market

  • 10.1. India No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 10.2. India No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 10.3. India No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 11.3. Japan No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 11.4. Japan No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

12. Australia No-Code Machine Learning Market

  • 12.1. Australia No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 12.2. Australia No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 12.3. Australia No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

13. Indonesia No-Code Machine Learning Market

  • 13.1. Indonesia No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 13.2. Indonesia No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 13.3. Indonesia No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 14.3. South Korea No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 14.4. South Korea No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 15.3. Western Europe No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 15.4. Western Europe No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

16. UK No-Code Machine Learning Market

  • 16.1. UK No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 16.2. UK No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 16.3. UK No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

17. Germany No-Code Machine Learning Market

  • 17.1. Germany No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 17.2. Germany No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 17.3. Germany No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

18. France No-Code Machine Learning Market

  • 18.1. France No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 18.2. France No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 18.3. France No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

19. Italy No-Code Machine Learning Market

  • 19.1. Italy No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 19.2. Italy No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 19.3. Italy No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

20. Spain No-Code Machine Learning Market

  • 20.1. Spain No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 20.2. Spain No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 20.3. Spain No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 21.3. Eastern Europe No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 21.4. Eastern Europe No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

22. Russia No-Code Machine Learning Market

  • 22.1. Russia No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 22.2. Russia No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 22.3. Russia No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 23.3. North America No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 23.4. North America No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 24.3. USA No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 24.4. USA No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 25.3. Canada No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 25.4. Canada No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 26.3. South America No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 26.4. South America No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion

27. Brazil No-Code Machine Learning Market

  • 27.1. Brazil No-Code Machine Learning Market, Segmentation By Offering, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 27.2. Brazil No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 27.3. Brazil No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 28.3. Middle East No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 28.4. Middle East No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 29.3. Africa No-Code Machine Learning Market, Segmentation By Deployment Mode, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ Billion
  • 29.4. Africa No-Code Machine Learning Market, Segmentation By Application, Historic and Forecast, 2018-2023, 2023-2028F, 2033F, $ 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
      • 30.2.1.1. Overview
      • 30.2.1.2. Products and Services
      • 30.2.1.3. Strategy
      • 30.2.1.4. Financial Performance
    • 30.2.2. Microsoft Azure Machine Learning Studio
      • 30.2.2.1. Overview
      • 30.2.2.2. Products and Services
      • 30.2.2.3. Strategy
      • 30.2.2.4. Financial Performance
    • 30.2.3. Amazon Web Services
      • 30.2.3.1. Overview
      • 30.2.3.2. Products and Services
      • 30.2.3.3. Strategy
      • 30.2.3.4. Financial Performance
    • 30.2.4. SAS Viya
      • 30.2.4.1. Overview
      • 30.2.4.2. Products and Services
      • 30.2.4.3. Strategy
      • 30.2.4.4. Financial Performance
    • 30.2.5. DataRobot Inc
      • 30.2.5.1. Overview
      • 30.2.5.2. Products and Services
      • 30.2.5.3. Strategy
      • 30.2.5.4. Financial Performance

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

33. Global No-Code Machine Learning Market Competitive Dashboard

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

35. No-Code Machine Learning Market Future Outlook and Potential Analysis

  • 35.1 No-Code Machine Learning Market In 2028 - Countries Offering Most New Opportunities
  • 35.2 No-Code Machine Learning Market In 2028 - Segments Offering Most New Opportunities
  • 35.3 No-Code Machine Learning Market In 2028 - 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