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ノーコード機械学習の世界市場レポート 2025年

No-Code Machine Learning Global Market Report 2025

出版日
ページ情報
英文 200 Pages
納期
2～10営業日
カスタマイズ可能
適宜更新あり
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価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=146.99円
ノーコード機械学習の世界市場レポート 2025年
出版日: 2025年04月03日
発行: The Business Research Company
ページ情報: 英文 200 Pages
納期: 2～10営業日
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  • 概要
  • 目次
概要

ノーコード機械学習市場規模は、今後数年で飛躍的な成長が見込まれます。2029年にはCAGR30.6％で42億1,000万米ドルに成長します。予測期間の成長は、利用しやすいAIツールに対する需要の高まり、さまざまな分野でのAI導入の増加、クラウドコンピューティングの採用拡大、事前構築された機械学習テンプレートの利用可能性の増加、技術スキルの障壁を減らすことへの注目の高まりに起因すると考えられます。予測期間における主な動向には、技術の進歩、AI主導のパーソナライゼーション、IoTアプリケーション、予測分析、セルフサービス分析などがあります。

モノのインターネット（IoT）の導入が進むことで、ノーコード機械学習市場の今後の成長が見込まれます。モノのインターネット（IoT）とは、インターネットを介して通信やデータ交換を行い、プロセスの自動化や業務効率の向上を図る相互接続されたデバイスやシステムのネットワークを指します。IoTの採用は、広範なデバイスやシステムを接続し最適化することで、業務効率を高め、リアルタイムのデータ洞察を提供し、自動化と遠隔監視を可能にし、コストを削減し、意思決定を改善し、さまざまな業界にわたってイノベーションを促進する能力によって推進されています。ノーコード機械学習は、IoTエコシステム内でますます活用され、豊富な技術的専門知識を必要とせずに機械学習モデルの作成、展開、管理を簡素化します。例えば、スウェーデンを拠点とするネットワーク・通信企業のエリクソンは2022年11月、世界のIoT接続デバイスの数が2022年の132億台から2028年には347億台に増加すると予測しました。その結果、IoT導入の増加がノーコード機械学習市場の拡大に拍車をかけています。

ノーコード機械学習市場の主要企業は、ノーコード機械学習ツールなど、ワークフローの自動化を強化する先進技術の開発に注力しています。これらのツールにより、ユーザーはコードを記述することなく機械学習モデルを作成・展開できるようになり、技術的な専門知識を持たないユーザーでもこの技術を利用しやすくなっています。例えば、米国のテクノロジー企業であるアマゾンは2023年12月、コーディング経験のないユーザーを対象としたノーコード機械学習ツール「SageMaker Canvas」を発表しました。このツールは、ビジネスアナリストや非技術系ユーザー向けに設計されており、モデル作成、データ準備、トレーニングを簡単に行えるユーザーフレンドリーなインターフェースを提供しています。SageMaker Canvasの主なアプリケーションには、顧客離れの予測、不正行為の検出、在庫の最適化などがあります。

目次

第1章 エグゼクティブサマリー

第2章 市場の特徴

第3章 市場動向と戦略

第4章 市場- 金利、インフレ、地政学、新型コロナウイルス感染症、そして景気回復が市場に与える影響を含むマクロ経済シナリオ

第5章 世界の成長分析と戦略分析フレームワーク

  • 世界ノーコード機械学習 PESTEL分析（政治、社会、技術、環境、法的要因、促進要因と抑制要因）
  • 最終用途産業の分析
  • 世界のノーコード機械学習市場：成長率分析
  • 世界のノーコード機械学習市場の実績：規模と成長, 2019-2024
  • 世界のノーコード機械学習市場の予測：規模と成長, 2024-2029, 2034F
  • 世界ノーコード機械学習総アドレス可能市場（TAM）

第6章 市場セグメンテーション

  • 世界のノーコード機械学習市場：提供別、実績と予測, 2019-2024, 2024-2029F, 2034F
  • プラットフォーム
  • サービス
  • 世界のノーコード機械学習市場：展開モード別、実績と予測, 2019-2024, 2024-2029F, 2034F
  • クラウドベース
  • オンプレミス
  • 世界のノーコード機械学習市場：業界別、実績と予測, 2019-2024, 2024-2029F, 2034F
  • 銀行、金融サービス、保険（BFSI）
  • ヘルスケア
  • 小売り
  • 情報技術（IT）と通信
  • 製造業
  • 政府
  • 世界のノーコード機械学習市場：用途別、実績と予測, 2019-2024, 2024-2029F, 2034F
  • 予測分析
  • プロセス自動化
  • データの可視化
  • ビジネスインテリジェンス
  • 顧客関係管理
  • サプライチェーンの最適化
  • 世界のノーコード機械学習市場プラットフォームのサブセグメンテーション（タイプ別）、実績と予測, 2019-2024, 2024-2029F, 2034F
  • 自動機械学習プラットフォーム（AutoML）
  • ドラッグアンドドロップ機械学習プラットフォーム
  • モデル展開プラットフォーム
  • データ準備プラットフォーム
  • 可視化およびレポートプラットフォーム
  • APIとデータソースの統合プラットフォーム
  • 世界のノーコード機械学習市場、サービスの種類別サブセグメンテーション、実績と予測, 2019-2024, 2024-2029F, 2034F
  • コンサルティングサービス
  • 実装サービス
  • 研修・教育サービス
  • サポートおよびメンテナンスサービス
  • カスタムソリューション開発サービス

第7章 地域別・国別分析

  • 世界のノーコード機械学習市場：地域別、実績と予測, 2019-2024, 2024-2029F, 2034F
  • 世界のノーコード機械学習市場：国別、実績と予測, 2019-2024, 2024-2029F, 2034F

第8章 アジア太平洋市場

第9章 中国市場

第10章 インド市場

第11章 日本市場

第12章 オーストラリア市場

第13章 インドネシア市場

第14章 韓国市場

第15章 西欧市場

第16章 英国市場

第17章 ドイツ市場

第18章 フランス市場

第19章 イタリア市場

第20章 スペイン市場

第21章 東欧市場

第22章 ロシア市場

第23章 北米市場

第24章 米国市場

第25章 カナダ市場

第26章 南米市場

第27章 ブラジル市場

第28章 中東市場

第29章 アフリカ市場

第30章 競合情勢と企業プロファイル

  • ノーコード機械学習市場：競合情勢
  • ノーコード機械学習市場：企業プロファイル
    • 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 その他の大手企業と革新的企業

  • 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 世界の市場競合ベンチマーキングとダッシュボード

第33章 主要な合併と買収

第34章 最近の市場動向

第35章 市場の潜在力が高い国、セグメント、戦略

  • ノーコード機械学習市場2029：新たな機会を提供する国
  • ノーコード機械学習市場2029：新たな機会を提供するセグメント
  • ノーコード機械学習市場2029：成長戦略
    • 市場動向に基づく戦略
    • 競合の戦略

第36章 付録

目次
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.
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  • Outperform competitors using forecast data and the drivers and trends shaping the market.
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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