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市场调查报告书
商品编码
1522792

全球无监督学习市场规模研究（按技术、部署模式、企业规模、最终用户和区域预测）2022-2032 年

Global Unsupervised Learning Market Size study, by Technology, by Deployment Mode, by Enterprise Size, by End User and Regional Forecasts 2022-2032
出版日期: | 出版商: Bizwit Research & Consulting LLP | 英文 200 Pages | 商品交期: 2-3个工作天内

价格
简介目录

2023 年全球无监督学习市场价值约为 42.7 亿美元，预计在 2024-2032 年预测期内将以超过 35.86% 的健康成长率成长。无监督学习是人工智慧和机器学习的一个子集，使系统能够在无需人工干预的情况下识别大量资料集中的模式和异常。这项技术在各个领域都具有巨大的前景，可促进异常检测、网路安全和自然语言处理等创新应用。

全球无监督学习市场是由大量且多样化的资料集激增所推动的，加上人工智慧和机器学习技术的不断进步，极大地推动了无监督学习市场的扩张。组织越来越多地利用这些技术从非结构化资料中获取可行的见解，从而提高营运效率和决策流程。此外，对强大的异常检测解决方案的需求不断增长以及对增强网路安全措施的需求为市场参与者提供了利润丰厚的机会。然而，与无监督学习模型相关的复杂性和缺乏可解释性将阻碍 2024-2032 年预测期内市场的整体需求。

全球无监督学习市场研究考虑的关键区域包括亚太地区、北美、欧洲、拉丁美洲和世界其他地区。 2023年，在机器学习和巨量资料分析等新兴技术的大量投资的推动下，北美占据了无监督学习市场的最大份额。该地区致力于将人工智慧和机器学习融入不同领域，为采用无监督学习技术创造了有利的环境。此外，由于 IT 基础设施的大量投资和智慧技术的采用，亚太地区预计将在预测期内实现最快的成长。该地区强调利用无监督学习进行模式识别和资料分析，凸显了其显着的市场扩张潜力。

目录

第 1 章：全球无监督学习市场执行摘要

  • 全球无监督学习市场规模及预测（2022-2032）
  • 区域概要
  • 分部摘要
    • 依技术
    • 按部署模式
    • 按企业规模
    • 按最终用户
  • 主要趋势
  • 经济衰退的影响
  • 分析师推荐与结论

第 2 章：全球无监督学习市场定义与研究假设

  • 研究目的
  • 市场定义
  • 研究假设
    • 包容与排除
    • 限制
    • 供给侧分析
      • 可用性
      • 基础设施
      • 监管环境
      • 市场竞争
      • 经济可行性（消费者的角度）
    • 需求面分析
      • 监理框架
      • 技术进步
      • 环境考虑
      • 消费者意识和接受度
  • 估算方法
  • 研究考虑的年份
  • 货币兑换率

第 3 章：全球无监督学习市场动态

  • 市场驱动因素
    • 庞大且多样化的资料集的可用性不断增长
    • 人工智慧和机器学习技术的进步
  • 市场挑战
    • 缺乏可解释性和可解释性
  • 市场机会
    • 对异常检测和网路安全的需求增加

第 4 章：全球无监督学习市场产业分析

  • 波特的五力模型
    • 供应商的议价能力
    • 买家的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争竞争
    • 波特五力模型的未来方法
    • 波特的五力影响分析
  • PESTEL分析
    • 政治的
    • 经济
    • 社会的
    • 技术性
    • 环境的
    • 合法的
  • 顶级投资机会
  • 最佳制胜策略
  • 颠覆性趋势
  • 产业专家视角
  • 分析师推荐与结论

第 5 章：2022-2032 年全球无监督学习市场规模与技术预测

  • 细分仪表板
  • 全球无监督学习市场：2022 年和 2032 年技术收入趋势分析
    • 自然语言处理（NLP）
    • 电脑视觉
    • 语音处理
    • 其他的

第 6 章：2022-2032 年全球无监督学习市场规模与部署模式预测

  • 细分仪表板
  • 全球无监督学习市场：2022 年和 2032 年部署模式收入趋势分析
    • 本地部署
    • 云

第 7 章：2022-2032 年全球无监督学习市场规模及企业规模预测

  • 细分仪表板
  • 全球无监督学习市场：2022 年和 2032 年企业规模收入趋势分析
    • 大型企业
    • 中小企业

第 8 章：2022-2032 年全球无监督学习市场规模与最终使用者预测

  • 细分仪表板
  • 全球无监督学习市场：2022 年和 2032 年最终用户收入趋势分析
    • BFSI
    • 资讯科技和电信
    • 零售及电子商务
    • 卫生保健
    • 政府
    • 汽车和交通
    • 其他的

第 9 章：2022-2032 年全球无监督学习市场规模及区域预测

  • 北美无监督学习市场
    • 美国无监督学习市场
      • 2022-2032 年技术细分规模与预测
      • 2022-2032 年部署模式细分规模与预测
      • 2022-2032 年企业规模细分规模与预测
      • 2022-2032 年最终用户细分规模与预测
    • 加拿大无监督学习市场
      • 2022-2032 年技术细分规模与预测
      • 2022-2032 年部署模式细分规模与预测
      • 2022-2032 年企业规模细分规模与预测
      • 2022-2032 年最终用户细分规模与预测
  • 欧洲无监督学习市场
    • 英国无监督学习市场
    • 德国无监督学习市场
    • 法国无监督学习市场
    • 西班牙无监督学习市场
    • 义大利无监督学习市场
    • 欧洲其他地区无监督学习市场
  • 亚太地区无监督学习市场
    • 中国无监督学习市场
    • 印度无监督学习市场
    • 日本无监督学习市场
    • 澳洲无监督学习市场
    • 韩国无监督学习市场
    • 亚太地区其他地区无监督学习市场
  • 拉丁美洲无监督学习市场
    • 巴西无监督学习市场
    • 墨西哥无监督学习市场
    • 拉丁美洲其他地区的无监督学习市场
  • 中东和非洲无监督学习市场
    • 沙乌地阿拉伯无监督学习市场
    • 南非无监督学习市场
    • 中东和非洲其他地区的无监督学习市场

第 10 章：竞争情报

  • 重点企业SWOT分析
  • 顶级市场策略
  • 公司简介
    • SAP SE
      • 关键讯息
      • 概述
      • 财务（视数据可用性而定）
      • 产品概要
      • 市场策略
    • Cloud Software Group, Inc.
    • Databricks
    • Microsoft Corporation
    • Google LLC
    • International Business Machines Corporation
    • RapidMiner
    • Oracle Corporation
    • H2O.ai
    • Amazon.com, Inc.

第 11 章：研究过程

  • 研究过程
    • 资料探勘
    • 分析
    • 市场预测
    • 验证
    • 出版
  • 研究属性
简介目录

Global Unsupervised Learning Market is valued approximately at USD 4.27 billion in 2023 and is anticipated to grow with a healthy growth rate of more than 35.86% over the forecast period 2024-2032. Unsupervised learning, a subset of artificial intelligence and machine learning, enables systems to identify patterns and anomalies within vast datasets without human intervention. This technology holds immense promise across various sectors, facilitating innovative applications such as anomaly detection, cybersecurity, and natural language processing.

The Global Unsupervised Learning Market is driven by proliferation of massive and varied datasets, coupled with continuous advancements in AI and machine learning techniques, is significantly propelling the expansion of the unsupervised learning market. Organizations are increasingly leveraging these technologies to derive actionable insights from unstructured data, thereby enhancing operational efficiencies and decision-making processes. Moreover, the escalating demand for robust anomaly detection solutions and the need for enhanced cybersecurity measures present lucrative opportunities for market players. However, the complexity and lack of interpretability associated with unsupervised learning models is going to impede the overall demand for the market during the forecast period 2024-2032.

The key regions considered for the Global Unsupervised Learning Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. In 2023, North America commanded the largest share of the unsupervised learning market, driven by substantial investments in emerging technologies such as machine learning and big data analytics. The region's focus on integrating AI and ML into diverse sectors has fostered a conducive environment for the adoption of unsupervised learning techniques. Furthermore, the Asia-Pacific region is poised for the fastest growth during the forecast period, attributed to significant investments in IT infrastructure and the adoption of smart technologies. The region's emphasis on leveraging unsupervised learning for pattern recognition and data analysis underscores its potential for remarkable market expansion.

Major market players included in this report are:

  • SAP SE
  • Cloud Software Group, Inc.
  • Databricks
  • Microsoft Corporation
  • Google LLC
  • International Business Machines Corporation
  • RapidMiner
  • Oracle Corporation
  • H2O.ai
  • Amazon.com, Inc

The detailed segments and sub-segment of the market are explained below:

By Technology:

  • Natural Language Processing (NLP)
  • Computer Vision
  • Speech Processing
  • Others

By Deployment Mode:

  • On-premise
  • Cloud

By Enterprise Size:

  • Large Enterprise
  • Small and Medium-sized Enterprise

By End User:

  • BFSI
  • IT and Telecom
  • Retail and E-commerce
  • Healthcare
  • Government
  • Automotive and Transportation
  • Others

By Region:

  • North America
  • U.S.
  • Canada
  • Europe
  • UK
  • Germany
  • France
  • Spain
  • Italy
  • ROE
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • RoAPAC
  • Latin America
  • Brazil
  • Mexico
  • Middle East & Africa
  • Saudi Arabia
  • South Africa
  • RoMEA

Years considered for the study are as follows:

  • Historical year - 2022
  • Base year - 2023
  • Forecast period - 2024 to 2032

Key Takeaways:

  • Market Estimates & Forecast for 10 years from 2022 to 2032.
  • Annualized revenues and regional level analysis for each market segment.
  • Detailed analysis of geographical landscape with Country level analysis of major regions.
  • Competitive landscape with information on major players in the market.
  • Analysis of key business strategies and recommendations on future market approach.
  • Analysis of competitive structure of the market.
  • Demand side and supply side analysis of the market

Table of Contents

Chapter 1. Global Unsupervised Learning Market Executive Summary

  • 1.1. Global Unsupervised Learning Market Size & Forecast (2022-2032)
  • 1.2. Regional Summary
  • 1.3. Segmental Summary
    • 1.3.1. By Technology
    • 1.3.2. By Deployment Mode
    • 1.3.3. By Enterprise Size
    • 1.3.4. By End User
  • 1.4. Key Trends
  • 1.5. Recession Impact
  • 1.6. Analyst Recommendation & Conclusion

Chapter 2. Global Unsupervised Learning Market Definition and Research Assumptions

  • 2.1. Research Objective
  • 2.2. Market Definition
  • 2.3. Research Assumptions
    • 2.3.1. Inclusion & Exclusion
    • 2.3.2. Limitations
    • 2.3.3. Supply Side Analysis
      • 2.3.3.1. Availability
      • 2.3.3.2. Infrastructure
      • 2.3.3.3. Regulatory Environment
      • 2.3.3.4. Market Competition
      • 2.3.3.5. Economic Viability (Consumer's Perspective)
    • 2.3.4. Demand Side Analysis
      • 2.3.4.1. Regulatory frameworks
      • 2.3.4.2. Technological Advancements
      • 2.3.4.3. Environmental Considerations
      • 2.3.4.4. Consumer Awareness & Acceptance
  • 2.4. Estimation Methodology
  • 2.5. Years Considered for the Study
  • 2.6. Currency Conversion Rates

Chapter 3. Global Unsupervised Learning Market Dynamics

  • 3.1. Market Drivers
    • 3.1.1. Growth in availability of huge and diverse datasets
    • 3.1.2. Advancements in artificial intelligence and machine learning techniques
  • 3.2. Market Challenges
    • 3.2.1. Lack of interpretability and explainability
  • 3.3. Market Opportunities
    • 3.3.1. Rise in demand for anomaly detection and cybersecurity

Chapter 4. Global Unsupervised Learning Market Industry Analysis

  • 4.1. Porter's 5 Force Model
    • 4.1.1. Bargaining Power of Suppliers
    • 4.1.2. Bargaining Power of Buyers
    • 4.1.3. Threat of New Entrants
    • 4.1.4. Threat of Substitutes
    • 4.1.5. Competitive Rivalry
    • 4.1.6. Futuristic Approach to Porter's 5 Force Model
    • 4.1.7. Porter's 5 Force Impact Analysis
  • 4.2. PESTEL Analysis
    • 4.2.1. Political
    • 4.2.2. Economical
    • 4.2.3. Social
    • 4.2.4. Technological
    • 4.2.5. Environmental
    • 4.2.6. Legal
  • 4.3. Top investment opportunity
  • 4.4. Top winning strategies
  • 4.5. Disruptive Trends
  • 4.6. Industry Expert Perspective
  • 4.7. Analyst Recommendation & Conclusion

Chapter 5. Global Unsupervised Learning Market Size & Forecasts by Technology 2022-2032

  • 5.1. Segment Dashboard
  • 5.2. Global Unsupervised Learning Market: Technology Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 5.2.1. Natural Language Processing (NLP)
    • 5.2.2. Computer Vision
    • 5.2.3. Speech Processing
    • 5.2.4. Others

Chapter 6. Global Unsupervised Learning Market Size & Forecasts by Deployment Mode 2022-2032

  • 6.1. Segment Dashboard
  • 6.2. Global Unsupervised Learning Market: Deployment Mode Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 6.2.1. On-premise
    • 6.2.2. Cloud

Chapter 7. Global Unsupervised Learning Market Size & Forecasts by Enterprise Size 2022-2032

  • 7.1. Segment Dashboard
  • 7.2. Global Unsupervised Learning Market: Enterprise Size Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 7.2.1. Large Enterprise
    • 7.2.2. Small and Medium-sized Enterprise

Chapter 8. Global Unsupervised Learning Market Size & Forecasts by End User 2022-2032

  • 8.1. Segment Dashboard
  • 8.2. Global Unsupervised Learning Market: End User Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 8.2.1. BFSI
    • 8.2.2. IT and Telecom
    • 8.2.3. Retail and E-commerce
    • 8.2.4. Healthcare
    • 8.2.5. Government
    • 8.2.6. Automotive and Transportation
    • 8.2.7. Others

Chapter 9. Global Unsupervised Learning Market Size & Forecasts by Region 2022-2032

  • 9.1. North America Unsupervised Learning Market
    • 9.1.1. U.S. Unsupervised Learning Market
      • 9.1.1.1. Technology breakdown size & forecasts, 2022-2032
      • 9.1.1.2. Deployment Mode breakdown size & forecasts, 2022-2032
      • 9.1.1.3. Enterprise Size breakdown size & forecasts, 2022-2032
      • 9.1.1.4. End User breakdown size & forecasts, 2022-2032
    • 9.1.2. Canada Unsupervised Learning Market
      • 9.1.2.1. Technology breakdown size & forecasts, 2022-2032
      • 9.1.2.2. Deployment Mode breakdown size & forecasts, 2022-2032
      • 9.1.2.3. Enterprise Size breakdown size & forecasts, 2022-2032
      • 9.1.2.4. End User breakdown size & forecasts, 2022-2032
  • 9.2. Europe Unsupervised Learning Market
    • 9.2.1. UK Unsupervised Learning Market
    • 9.2.2. Germany Unsupervised Learning Market
    • 9.2.3. France Unsupervised Learning Market
    • 9.2.4. Spain Unsupervised Learning Market
    • 9.2.5. Italy Unsupervised Learning Market
    • 9.2.6. Rest of Europe Unsupervised Learning Market
  • 9.3. Asia-Pacific Unsupervised Learning Market
    • 9.3.1. China Unsupervised Learning Market
    • 9.3.2. India Unsupervised Learning Market
    • 9.3.3. Japan Unsupervised Learning Market
    • 9.3.4. Australia Unsupervised Learning Market
    • 9.3.5. South Korea Unsupervised Learning Market
    • 9.3.6. Rest of Asia Pacific Unsupervised Learning Market
  • 9.4. Latin America Unsupervised Learning Market
    • 9.4.1. Brazil Unsupervised Learning Market
    • 9.4.2. Mexico Unsupervised Learning Market
    • 9.4.3. Rest of Latin America Unsupervised Learning Market
  • 9.5. Middle East & Africa Unsupervised Learning Market
    • 9.5.1. Saudi Arabia Unsupervised Learning Market
    • 9.5.2. South Africa Unsupervised Learning Market
    • 9.5.3. Rest of Middle East & Africa Unsupervised Learning Market

Chapter 10. Competitive Intelligence

  • 10.1. Key Company SWOT Analysis
  • 10.2. Top Market Strategies
  • 10.3. Company Profiles
    • 10.3.1. SAP SE
      • 10.3.1.1. Key Information
      • 10.3.1.2. Overview
      • 10.3.1.3. Financial (Subject to Data Availability)
      • 10.3.1.4. Product Summary
      • 10.3.1.5. Market Strategies
    • 10.3.2. Cloud Software Group, Inc.
    • 10.3.3. Databricks
    • 10.3.4. Microsoft Corporation
    • 10.3.5. Google LLC
    • 10.3.6. International Business Machines Corporation
    • 10.3.7. RapidMiner
    • 10.3.8. Oracle Corporation
    • 10.3.9. H2O.ai
    • 10.3.10. Amazon.com, Inc.

Chapter 11. Research Process

  • 11.1. Research Process
    • 11.1.1. Data Mining
    • 11.1.2. Analysis
    • 11.1.3. Market Estimation
    • 11.1.4. Validation
    • 11.1.5. Publishing
  • 11.2. Research Attributes