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自动化机器学习解决方案市场 - 2018-2028 年全球产业规模、份额、趋势、机会和预测，按产品、部署、自动化类型、企业规模、最终用户、地区和竞争进行细分

Automated Machine Learning Solution Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028 Segmented By Offering, By Deployment, By Automation Type, By Enterprise Size, By End-Users, By Region and Competition
出版日期: | 出版商: TechSci Research | 英文 185 Pages | 商品交期: 2-3个工作天内

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简介目录

预计全球自动化机器学习解决方案市场将在 2023-2028 年预测期内蓬勃发展。使用预测线索评分系统进行客户细分和瞄准潜在消费者正在增加全球对自动化机器学习 (AutoML) 解决方案的需求。

该行业的许多领域现在严重依赖机器学习 (ML)。另一方面，开发高性能机器学习系统需要高度专业化的资料科学家和主题专家。透过使领域专家能够自动创建机器学习应用程序，而无需大量的统计和机器学习技能，自动化机器学习 (AutoML) 旨在减少对资料科学家的需求。资料科学和人工智慧的进步提高了自动化机器学习的性能。由于企业看到了这项技术的前景，因此其采用率预计在预估期间内将会增加。客户现在可以更轻鬆地使用自动化机器学习解决方案，因为企业将其作为订阅服务出售。此外，它还提供按需付费的灵活性。

最近，机器学习 (ML) 在各种应用中得到越来越多的使用，但没有足够的机器学习专业人员来跟上这种成长。自动化机器学习 (AutoML) 的目标是让机器学习变得更平易近人。因此，专业人士应该能够安装更多的机器学习系统，并且使用 AutoML 比直接使用 ML 需要更少的技能。然而，该技术目前的接受程度还不够，这限制了全球自动化机器学习解决方案市场的扩张。

市场概况
预测期 2024-2028
2022 年市场规模 11.2亿美元
2028 年市场规模 93.4亿美元
2023-2028 年复合年增长率 42.48%
成长最快的细分市场 製造业
最大的市场 北美洲

COVID-19 疫情之后，组织越来越依赖智慧解决方案来实现业务营运自动化，这导致人工智慧的使用增加。预计这种模式将在接下来的几年中持续存在，从而加速人工智慧在业务运营中的采用。

对高效诈欺检测解决方案的需求不断增长

机器学习广泛应用于金融应用，包括交易、流程自动化、信用评分以及贷款和保险承保。金融安全的主要问题之一是金融诈欺。机器学习目前正用于诈欺侦测应用，以应对日益严重的金融诈欺危险。为了利用最近获得的数位管道获取的大量资料，金融服务领域的几家公司现在正在积极将人工智慧和机器学习整合到其生态系统中。疫情带来的客户行为和优先事项的范式变化也促进了其扩张，导致 54% 的员工人数超过 5,000 人的金融服务公司将技术整合到其业务实践中。企业越来越需要一种诈骗侦测系统，该系统可以在接受线上信用卡付款时提供即时且可操作的警告。这些因素正在推动全球自动化机器学习解决方案市场的发展。

对智慧业务流程的需求正在上升

随着企业现在转向利用下一代技术，人工智慧 (AI) 的使用正在增加。企业可以将人工智慧用于多种目的，包括资料收集和工作流程效率。由于人工智慧分析在现成的 CRM 平台中广泛使用，销售团队现在可以按需提供富有洞察力的资料。例如，Salesforce 的 Einstein AI 技术可以预测哪些客户最有可能增加销售并更换品牌。有了这样的讯息，销售人员就可以将时间和精力集中在最重要的地方。此外，企业越来越重视评估和改进客户服务，这促进了组织内基于人工智慧的流程的扩展。它使企业能够更好地了解消费者偏好和购买趋势，从而使他们能够提供量身定制的产品建议。由于机器人技术在包括製造和仓储等在内的各个行业中不断扩大部署，对人工智慧的需求正在增加。透过机器视觉等人工智慧技术，协作机器人能够了解周遭的人。他们可以做出适当的反应，例如放慢速度或转身避开人群。因此，可以创建流程来最大限度地发挥人和机器人的能力。

自动化机器学习工具的采用缓慢

机器学习 (ML) 正在越来越多的应用中使用，但没有足够的机器学习专家来跟上这种扩充功能。自动化机器学习 (AutoML) 的目标是让机器学习变得更平易近人。因此，专家应该能够安装更多的机器学习系统，并且使用 AutoML 所需的技能比直接处理 ML 所需的技能要少。然而，目前该技术的接受度还不够高，这限制了自动化机器学习解决方案市场的扩张。首先，有一种误解，认为 AutoML 方法很难使用，并且需要大量的初始投资才能了解如何使用它们。其次，AutoML 系统偶尔会在处理使用者资料时遇到问题，但并不总是能识别问题。人们也担心使用 AutoML 所需的处理能力。

不断增长的医疗保健应用

医疗保健领域的许多应用已经利用了机器学习技术。该平台分析该垂直行业的数百万个不同资料点，预测结果，并提供快速风险评估和精确的资源分配。

使用者对自动化机器学习解决方案的抵制

市场延迟采用自动化机器学习解决方案主要是由于机器学习技术的采用有限。公司很难获得他们所需的领域专家，因为对机器学习适当能力的需求很大。此外，由于聘用这些专业人员的成本很高，企业更不可能采用机器学习等尖端技术。最终使用者的类型也可能会影响对使用 AutoML 技术的抵制。例如，考虑到政府组织管理公民资料，他们可能会抵制使用自动化机器学习解决方案。因此，对隐私和资料敏感度的担忧可能会阻止他们使用此类解决方案，从而减缓市场的扩张。此外，由于技术的限制，人们不愿意使用此类工具，一些行业专业人士已经注意到这一点。这些都是 AutoML 遇到的资料和模型应用问题。例如，离线资料处理过程中资料不一致、标记资料品质不够高等都会产生负面影响。此外，团队必须对非结构化和半结构化资料进行技术要求很高的自动化机器学习处理。

市场区隔

自动化机器学习解决方案市场分为产品、部署、自动化类型、企业规模、最终用户、公司和地区。依产品提供，市场分为平台与服务。根据部署，市场分为本地和云端。根据自动化类型，市场分为资料处理、特征工程、建模和视觉化。根据企业规模，市场分为大型企业和中小企业。根据最终用户，市场分为 BFSI、零售和电子商务、医​​疗保健和製造业。按地区划分，市场分为北美、亚太地区、欧洲、南美、中东和非洲

市场参与者

全球自动化机器学习解决方案市场的一些主要市场参与者包括 Datarobot Inc.、Amazon Web Services Inc.、dotData Inc.、IBM Corporation、Dataiku、EdgeVerve Systems Limited、Big Squid Inc.、SAS Institute Inc.、微软公司、 Determine.ai Inc.

报告范围：

在本报告中，除了下面详细介绍的产业趋势外，全球自动化机器学习解决方案市场还分为以下几类：

自动化机器学习解决方案市场，透过提供

  • 平台
  • 服务

自动化机器学习解决方案市场（按部署）：

  • 本地部署
  • 云

自动化机器学习解决方案市场（按自动化类型）：

  • 资料处理
  • 特征工程
  • 造型
  • 视觉化

自动化机器学习解决方案市场，依企业规模划分：

  • 大型企业
  • 中小企业

自动化机器学习解决方案市场，按最终用户划分：

  • BFSI
  • 零售与电子商务
  • 卫生保健
  • 製造业

自动化机器学习解决方案市场（按地区）：

  • 北美洲
  • 美国
  • 加拿大
  • 墨西哥
  • 亚太
  • 印度
  • 中国
  • 日本
  • 韩国
  • 澳洲
  • 新加坡
  • 马来西亚
  • 欧洲
  • 德国
  • 英国
  • 法国
  • 俄罗斯
  • 西班牙
  • 比利时
  • 义大利
  • 南美洲
  • 巴西
  • 阿根廷
  • 哥伦比亚
  • 秘鲁
  • 智利
  • 中东
  • 沙乌地阿拉伯
  • 南非
  • 阿联酋
  • 以色列
  • 土耳其

竞争格局

  • 公司简介：详细分析全球自动化机器学习解决方案市场中的主要公司。

可用的客製化：

  • 全球自动化机器学习解决方案市场报告以及给定的市场资料，Tech Sci Research 根据公司的具体需求提供客製化服务。该报告可以使用以下自订选项：

公司资讯

  • 其他市场参与者（最多五个）的详细分析和概况分析。

目录

第 1 章：服务概述

第 2 章：研究方法

第 3 章：COVID-19 对全球自动化机器学习解决方案市场的影响

第 4 章：执行摘要

第 5 章：客户之声

第 6 章：全球自动化机器学习解决方案市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按产品提供（平台、服务）
    • 按部署（本地、云端）
    • 依自动化类型（资料处理、特征工程、建模、视觉化）
    • 依企业规模（大型企业、中小企业）
    • 按最终用户（BFSI、零售和电子商务、医​​疗保健、製造业）
    • 按地区
  • 按公司划分 (2022)
  • 市场地图

第 7 章：北美自动化机器学习解决方案市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过提供
    • 按部署
    • 按自动化类型
    • 按企业规模
    • 由最终用户
    • 按国家/地区
  • 北美：国家分析
    • 美国
    • 加拿大
    • 墨西哥

第 8 章：亚太地区自动化机器学习解决方案市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过提供
    • 按部署
    • 按自动化类型
    • 按企业规模
    • 由最终用户
    • 按国家/地区
  • 亚太地区：国家分析
    • 中国
    • 印度
    • 日本
    • 韩国
    • 澳洲
    • 新加坡
    • 马来西亚

第 9 章：欧洲自动化机器学习解决方案市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过提供
    • 按部署
    • 按自动化类型
    • 按企业规模
    • 由最终用户
    • 按国家/地区
  • 欧洲：国家分析
    • 德国
    • 英国
    • 法国
    • 俄罗斯
    • 西班牙
    • 比利时
    • 义大利

第 10 章：南美洲自动化机器学习解决方案市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过提供
    • 按部署
    • 按自动化类型
    • 按企业规模
    • 由最终用户
    • 按国家/地区
  • 南美洲：国家分析
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 秘鲁
    • 智利

第 11 章：中东和非洲自动化机器学习解决方案市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 透过提供
    • 按部署
    • 按自动化类型
    • 按企业规模
    • 由最终用户
    • 按国家/地区
  • 中东和非洲：国家分析
    • 沙乌地阿拉伯
    • 南非
    • 阿联酋
    • 以色列
    • 土耳其

第 12 章：市场动态

  • 司机
  • 挑战

第 13 章：市场趋势与发展

第 14 章：公司简介

  • 数据机器人公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 亚马逊网路服务公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 点数据公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • IBM公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 达泰库
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • EdgeVerve系统有限公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 大鱿鱼公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • SAS 研究所公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 微软公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 确定.ai公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services

第 15 章：策略建议

第 16 章：关于我们与免责声明

简介目录
Product Code: 15569

Global automated machine learning solution market is anticipated to thrive in the forecast period 2023-2028. The usage of predictive lead scoring systems for customer segmentation and targeting potential consumers is rising the demand for the automated machine learning (AutoML) solutions across the globe.

Many areas of the industry now depend heavily on machine learning (ML). On the other hand, developing high-performance machine learning systems requires highly specialised data scientists and subject matter specialists. By enabling domain experts to automatically create machine learning applications without extensive statistical and machine learning skills, automated machine learning (AutoML) aims to reduce the need for data scientists. The advancements in data science and artificial intelligence have improved automated machine learning's performance. Because businesses see this technology's promise, its adoption rate is expected to increase during the projected period. Customers may now employ automated machine learning solutions more easily since businesses are selling them as subscription services. Additionally, it provides pay-as-you-go flexibility.

Machine learning (ML) is being utilised more often in a variety of applications lately, but there aren't enough machine learning professionals to keep up with this increase. The goal of automated machine learning (AutoML) is to make machine learning more approachable. As a result, professionals should be able to install more machine learning systems, and using AutoML would need less skill than using ML directly. The technology's acceptance, nevertheless, is currently only moderate, which limits the global automated machine learning solution market expansion.

Market Overview
Forecast Period2024-2028
Market Size 2022USD 1.12 Billion
Market Size 2028USD 9.34 Billion
CAGR 2023-202842.48%
Fastest Growing SegmentManufacturing
Largest MarketNorth America

After the COVID-19 epidemic, organisations have been increasingly relying on intelligent solutions to automate their business operations, which is causing a rise in the use of AI. This pattern is anticipated to persist throughout the ensuing years, accelerating the adoption of AI in business operations.

Increasing Demand for Efficient Fraud Detection Solutions

Machine learning is used in a wide range of financial applications, including trading, process automation, credit scoring, and underwriting for loans and insurance. One of the major issues with financial security is financial fraud. Machine learning is currently being used for fraud detection applications to combat the rising danger of financial fraud. In order to make use of the massive data accessible from recently acquired digital channels, several firms in the financial services sector are now actively integrating AI and ML into their ecosystems. A paradigm change in customer behaviour and priorities brought about by the pandemic has also boosted its expansion, leading 54% of financial services companies with more least 5,000 workers to integrate the technology into their business practises. Businesses are increasingly in need of a fraud detection system that can provide real-time and actionable warnings as they progress towards accepting credit card payments online. These factors are driving the global automated machine learning solution market.

Demand for Intelligent Business Processes is Rising

Artificial Intelligence (AI) usage is increasing as businesses now turn to utilising next-generation technology. Businesses may employ artificial intelligence for a variety of purposes, including data collection and work process efficiency. As a result of the widespread use of AI analytics in off-the-shelf CRM platforms, sales teams can now provide insightful data on demand. Salesforce's Einstein AI technology, for instance, can forecast which customers are most likely to increase sales and to switch brands. With information like this, salespeople can concentrate their time and efforts where it counts the most. Additionally, the growing emphasis that businesses are placing on evaluating and improving customer services is fostering the expansion of AI-based processes within organisations. It gives businesses improved understanding of consumer preferences and purchasing trends, which in turn enables them to provide tailored product suggestions. The need for AI is rising as a result of the expanding deployment of robotics across a variety of industries, including manufacturing and warehousing, among others. Co-bots are aware of the people around them because to AI technologies like machine vision. They can respond appropriately, for instance by slowing down or turning around to avoid people. As a result, processes may be created to maximise the capabilities of both people and robots.

Slow Adoption of Automated Machine Learning Tools

Machine learning (ML) is being employed in a growing number of applications, but there aren't enough machine learning specialists to keep up with this expansion. The goal of automated machine learning (AutoML) is to make machine learning more approachable. As a result, specialists should be able to install more machine learning systems, and working with AutoML would need less skill than dealing with ML directly. The technology's acceptance, nevertheless, is currently moderate, which limits the automated machine learning solution market's expansion. First, there is a misconception that AutoML approaches are difficult to use and would demand a substantial initial investment to understand how to utilise them. Secondly, autoML systems occasionally have trouble working with user data but don't always identify the issue.. Concerns were also raised over the amount of processing power needed to use AutoML.

Growing Healthcare Applications

Many applications in the field of healthcare already make use of machine learning technology. This platform analyses millions of different data points from this sector vertical, forecasts results, and also offers rapid risk assessments and precise resource allocation.

The ability to diagnose and identify disorders and illnesses that might occasionally be challenging to recognise is one of this technology's most significant uses in healthcare. This can include a number of inherited conditions and tumours that are challenging to identify in the first stages. The IBM Watson Genomics is a notable illustration of this, demonstrating how genome-based tumour sequencing in conjunction with cognitive computing may facilitate cancer detection.

A major biopharmaceutical company called Berg, uses AI to provide medicinal treatments for diseases like cancer. All these factors are driving the market of global automated machine learning solution market.

Resistance among Users Regarding Automated Machine Learning Solutions

The market's delayed adoption of automated machine learning solutions is mostly due to the limited uptake of machine learning technologies. Companies struggle to obtain the domain experts they need since there is a significant demand for them in the machine learning proper ability. Additionally, because it is expensive to hire these professionals, businesses are even less likely to adopt cutting-edge technology like machine learning. The sorts of end users may also affect the resistance to using AutoML technologies. For instance, given that they manage citizen data, government organisations may show resistance to using automated machine learning solutions. As a result, concerns over privacy and the sensitivity of data may deter them from using such solutions, slowing the market's expansion. Additionally, people are reluctant to utilise such tools due to the limits of the technology, which have been noted by several industry professionals. These are issues with data and model application that AutoML encounters. For instance, inconsistent data during offline data processing and insufficiently high-quality labelled data would have negative impacts. Additionally, teams must do technical-demanding automated machine learning processing of unstructured and semi-structured data.

Market Segmentation

The automated machine learning solution market is segmented into offering, deployment, automation type, enterprise size, end-users, company, and region. Based on offering, the market is segmented into platform and service. Based on deployment, the market is segmented into on-premise and cloud. Based on automation type, the market is segmented into data processing, feature engineering, modeling, and visualization. Based on enterprise size, the market is segmented into large enterprise and SMEs. Based on end-users, the market is segmented into BFSI, retail and e-commerce, healthcare, and manufacturing. Based on region, the market is segmented into North America, Asia-Pacific, Europe, South America, and Middle East & Africa

Market Players

Some of the major market players in the global automated machine learning solution market are Datarobot Inc., Amazon Web Services Inc., dotData Inc., IBM Corporation, Dataiku, EdgeVerve Systems Limited, Big Squid Inc., SAS Institute Inc., Microsoft Corporation, and Determined.ai Inc.

Report Scope:

In this report, the global automated machine learning solution market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Automated Machine Learning Solution Market, By Offering

  • Platform
  • Service

Automated Machine Learning Solution Market, By Deployment:

  • On-Premise
  • Cloud

Automated Machine Learning Solution Market, By Automation Type:

  • Data Processing
  • Feature Engineering
  • Modeling
  • Visualization

Automated Machine Learning Solution Market, By Enterprise Size:

  • Large Enterprises
  • SMEs

Automated Machine Learning Solution Market, By End-users:

  • BFSI
  • Retail and E-Commerce
  • Healthcare
  • Manufacturing

Automated Machine Learning Solution Market, By Region:

  • North America
  • United States
  • Canada
  • Mexico
  • Asia-Pacific
  • India
  • China
  • Japan
  • South Korea
  • Australia
  • Singapore
  • Malaysia
  • Europe
  • Germany
  • United Kingdom
  • France
  • Russia
  • Spain
  • Belgium
  • Italy
  • South America
  • Brazil
  • Argentina
  • Colombia
  • Peru
  • Chile
  • Middle East
  • Saudi Arabia
  • South Africa
  • UAE
  • Israel
  • Turkey

Competitive Landscape

  • Company Profiles: Detailed analysis of the major companies present in the global automated machine learning solution market.

Available Customizations:

  • Global automated machine learning solution market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Service Overview

2. Research Methodology

3. Impact of COVID-19 on Global Automated Machine Learning Solution Market

4. Executive Summary

5. Voice of Customers

6. Global Automated Machine Learning Solution Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Offering( Platform, Service)
    • 6.2.2. By Deployment (On-Premise, Cloud)
    • 6.2.3. By Automation Type (Data Processing, Feature Engineering, Modeling, Visualization)
    • 6.2.4. By Enterprise Size(Large Enterprises, SMEs)
    • 6.2.5. By End-users (BFSI, Retail and E-Commerce, Healthcare, Manufacturing)
    • 6.2.6. By Region
  • 6.3. By Company (2022)
  • 6.4. Market Map

7. North America Automated Machine Learning Solution Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Offering
    • 7.2.2. By Deployment
    • 7.2.3. By Automation Type
    • 7.2.4. By Enterprise Size
    • 7.2.5. By End-users
    • 7.2.6. By Country
  • 7.3. North America: Country Analysis
    • 7.3.1. United States Automated Machine Learning Solution Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Offering
        • 7.3.1.2.2. By Deployment
        • 7.3.1.2.3. By Automation Type
        • 7.3.1.2.4. By Enterprise Size
        • 7.3.1.2.5. By End-users
    • 7.3.2. Canada Automated Machine Learning Solution Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Offering
        • 7.3.2.2.2. By Deployment
        • 7.3.2.2.3. By Automation Type
        • 7.3.2.2.4. By Enterprise Size
        • 7.3.2.2.5. By End-users
    • 7.3.3. Mexico Automated Machine Learning Solution Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Offering
        • 7.3.3.2.2. By Deployment
        • 7.3.3.2.3. By Automation Type
        • 7.3.3.2.4. By Enterprise Size
        • 7.3.3.2.5. By End-users

8. Asia-Pacific Automated Machine Learning Solution Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Offering
    • 8.2.2. By Deployment
    • 8.2.3. By Automation Type
    • 8.2.4. By Enterprise Size
    • 8.2.5. By End-users
    • 8.2.6. By Country
  • 8.3. Asia-Pacific: Country Analysis
    • 8.3.1. China Automated Machine Learning Solution Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Offering
        • 8.3.1.2.2. By Deployment
        • 8.3.1.2.3. By Automation Type
        • 8.3.1.2.4. By Enterprise Size
        • 8.3.1.2.5. By End-users
    • 8.3.2. India Automated Machine Learning Solution Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Offering
        • 8.3.2.2.2. By Deployment
        • 8.3.2.2.3. By Automation Type
        • 8.3.2.2.4. By Enterprise Size
        • 8.3.2.2.5. By End-users
    • 8.3.3. Japan Automated Machine Learning Solution Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Offering
        • 8.3.3.2.2. By Deployment
        • 8.3.3.2.3. By Automation Type
        • 8.3.3.2.4. By Enterprise Size
        • 8.3.3.2.5. By End-users
    • 8.3.4. South Korea Automated Machine Learning Solution Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Offering
        • 8.3.4.2.2. By Deployment
        • 8.3.4.2.3. By Automation Type
        • 8.3.4.2.4. By Enterprise Size
        • 8.3.4.2.5. By End-users
    • 8.3.5. Australia Automated Machine Learning Solution Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Offering
        • 8.3.5.2.2. By Deployment
        • 8.3.5.2.3. By Automation Type
        • 8.3.5.2.4. By Enterprise Size
        • 8.3.5.2.5. By End-users
    • 8.3.6. Singapore Automated Machine Learning Solution Market Outlook
      • 8.3.6.1. Market Size & Forecast
        • 8.3.6.1.1. By Value
      • 8.3.6.2. Market Share & Forecast
        • 8.3.6.2.1. By Offering
        • 8.3.6.2.2. By Deployment
        • 8.3.6.2.3. By Automation Type
        • 8.3.6.2.4. By Enterprise Size
        • 8.3.6.2.5. By End-users
    • 8.3.7. Malaysia Automated Machine Learning Solution Market Outlook
      • 8.3.7.1. Market Size & Forecast
        • 8.3.7.1.1. By Value
      • 8.3.7.2. Market Share & Forecast
        • 8.3.7.2.1. By Offering
        • 8.3.7.2.2. By Deployment
        • 8.3.7.2.3. By Automation Type
        • 8.3.7.2.4. By Enterprise Size
        • 8.3.7.2.5. By End-users

9. Europe Automated Machine Learning Solution Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Offering
    • 9.2.2. By Deployment
    • 9.2.3. By Automation Type
    • 9.2.4. By Enterprise Size
    • 9.2.5. By End-users
    • 9.2.6. By Country
  • 9.3. Europe: Country Analysis
    • 9.3.1. Germany Automated Machine Learning Solution Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Offering
        • 9.3.1.2.2. By Deployment
        • 9.3.1.2.3. By Automation Type
        • 9.3.1.2.4. By Enterprise Size
        • 9.3.1.2.5. By End-users
    • 9.3.2. United Kingdom Automated Machine Learning Solution Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Offering
        • 9.3.2.2.2. By Deployment
        • 9.3.2.2.3. By Automation Type
        • 9.3.2.2.4. By Enterprise Size
        • 9.3.2.2.5. By End-users
    • 9.3.3. France Automated Machine Learning Solution Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Offering
        • 9.3.3.2.2. By Deployment
        • 9.3.3.2.3. By Automation Type
        • 9.3.3.2.4. By Enterprise Size
        • 9.3.3.2.5. By End-users
    • 9.3.4. Russia Automated Machine Learning Solution Market Outlook
      • 9.3.4.1. Market Size & Forecast
        • 9.3.4.1.1. By Value
      • 9.3.4.2. Market Share & Forecast
        • 9.3.4.2.1. By Offering
        • 9.3.4.2.2. By Deployment
        • 9.3.4.2.3. By Automation Type
        • 9.3.4.2.4. By Enterprise Size
        • 9.3.4.2.5. By End-users
    • 9.3.5. Spain Automated Machine Learning Solution Market Outlook
      • 9.3.5.1. Market Size & Forecast
        • 9.3.5.1.1. By Value
      • 9.3.5.2. Market Share & Forecast
        • 9.3.5.2.1. By Offering
        • 9.3.5.2.2. By Deployment
        • 9.3.5.2.3. By Automation Type
        • 9.3.5.2.4. By Enterprise Size
        • 9.3.5.2.5. By End-users
    • 9.3.6. Belgium Automated Machine Learning Solution Market Outlook
      • 9.3.6.1. Market Size & Forecast
        • 9.3.6.1.1. By Value
      • 9.3.6.2. Market Share & Forecast
        • 9.3.6.2.1. By Offering
        • 9.3.6.2.2. By Deployment
        • 9.3.6.2.3. By Automation Type
        • 9.3.6.2.4. By Enterprise Size
        • 9.3.6.2.5. By End-users
    • 9.3.7. Italy Automated Machine Learning Solution Market Outlook
      • 9.3.7.1. Market Size & Forecast
        • 9.3.7.1.1. By Value
      • 9.3.7.2. Market Share & Forecast
        • 9.3.7.2.1. By Offering
        • 9.3.7.2.2. By Deployment
        • 9.3.7.2.3. By Automation Type
        • 9.3.7.2.4. By Enterprise Size
        • 9.3.7.2.5. By End-users

10. South America Automated Machine Learning Solution Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Offering
    • 10.2.2. By Deployment
    • 10.2.3. By Automation Type
    • 10.2.4. By Enterprise Size
    • 10.2.5. By End-users
    • 10.2.6. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Automated Machine Learning Solution Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Offering
        • 10.3.1.2.2. By Deployment
        • 10.3.1.2.3. By Automation Type
        • 10.3.1.2.4. By Enterprise Size
        • 10.3.1.2.5. By End-users
    • 10.3.2. Argentina Automated Machine Learning Solution Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Offering
        • 10.3.2.2.2. By Deployment
        • 10.3.2.2.3. By Automation Type
        • 10.3.2.2.4. By Enterprise Size
        • 10.3.2.2.5. By End-users
    • 10.3.3. Colombia Automated Machine Learning Solution Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Offering
        • 10.3.3.2.2. By Deployment
        • 10.3.3.2.3. By Automation Type
        • 10.3.3.2.4. By Enterprise Size
        • 10.3.3.2.5. By End-users
    • 10.3.4. Peru Automated Machine Learning Solution Market Outlook
      • 10.3.4.1. Market Size & Forecast
        • 10.3.4.1.1. By Value
      • 10.3.4.2. Market Share & Forecast
        • 10.3.4.2.1. By Offering
        • 10.3.4.2.2. By Deployment
        • 10.3.4.2.3. By Automation Type
        • 10.3.4.2.4. By Enterprise Size
        • 10.3.4.2.5. By End-users
    • 10.3.5. Chile Automated Machine Learning Solution Market Outlook
      • 10.3.5.1. Market Size & Forecast
        • 10.3.5.1.1. By Value
      • 10.3.5.2. Market Share & Forecast
        • 10.3.5.2.1. By Offering
        • 10.3.5.2.2. By Deployment
        • 10.3.5.2.3. By Automation Type
        • 10.3.5.2.4. By Enterprise Size
        • 10.3.5.2.5. By End-users

11. Middle East & Africa Automated Machine Learning Solution Market Outlook

  • 11.1. Market Size & Forecast
    • 11.1.1. By Value
  • 11.2. Market Share & Forecast
    • 11.2.1. By Offering
    • 11.2.2. By Deployment
    • 11.2.3. By Automation Type
    • 11.2.4. By Enterprise Size
    • 11.2.5. By End-users
    • 11.2.6. By Country
  • 11.3. Middle East & Africa: Country Analysis
    • 11.3.1. Saudi Arabia Automated Machine Learning Solution Market Outlook
      • 11.3.1.1. Market Size & Forecast
        • 11.3.1.1.1. By Value
      • 11.3.1.2. Market Share & Forecast
        • 11.3.1.2.1. By Offering
        • 11.3.1.2.2. By Deployment
        • 11.3.1.2.3. By Automation Type
        • 11.3.1.2.4. By Enterprise Size
        • 11.3.1.2.5. By End-users
    • 11.3.2. South Africa Automated Machine Learning Solution Market Outlook
      • 11.3.2.1. Market Size & Forecast
        • 11.3.2.1.1. By Value
      • 11.3.2.2. Market Share & Forecast
        • 11.3.2.2.1. By Offering
        • 11.3.2.2.2. By Deployment
        • 11.3.2.2.3. By Automation Type
        • 11.3.2.2.4. By Enterprise Size
        • 11.3.2.2.5. By End-users
    • 11.3.3. UAE Automated Machine Learning Solution Market Outlook
      • 11.3.3.1. Market Size & Forecast
        • 11.3.3.1.1. By Value
      • 11.3.3.2. Market Share & Forecast
        • 11.3.3.2.1. By Offering
        • 11.3.3.2.2. By Deployment
        • 11.3.3.2.3. By Automation Type
        • 11.3.3.2.4. By Enterprise Size
        • 11.3.3.2.5. By End-users
    • 11.3.4. Israel Automated Machine Learning Solution Market Outlook
      • 11.3.4.1. Market Size & Forecast
        • 11.3.4.1.1. By Value
      • 11.3.4.2. Market Share & Forecast
        • 11.3.4.2.1. By Offering
        • 11.3.4.2.2. By Deployment
        • 11.3.4.2.3. By Automation Type
        • 11.3.4.2.4. By Enterprise Size
        • 11.3.4.2.5. By End-users
    • 11.3.5. Turkey Automated Machine Learning Solution Market Outlook
      • 11.3.5.1. Market Size & Forecast
        • 11.3.5.1.1. By Value
      • 11.3.5.2. Market Share & Forecast
        • 11.3.5.2.1. By Offering
        • 11.3.5.2.2. By Deployment
        • 11.3.5.2.3. By Automation Type
        • 11.3.5.2.4. By Enterprise Size
        • 11.3.5.2.5. By End-users

12. Market Dynamics

  • 12.1. Drivers
  • 12.2. Challenges

13. Market Trends & Developments

14. Company Profiles

  • 14.1. Datarobot Inc.
    • 14.1.1. Business Overview
    • 14.1.2. Key Revenue and Financials
    • 14.1.3. Recent Developments
    • 14.1.4. Key Personnel
    • 14.1.5. Key Product/Services
  • 14.2. Amazon Web Services Inc.
    • 14.2.1. Business Overview
    • 14.2.2. Key Revenue and Financials
    • 14.2.3. Recent Developments
    • 14.2.4. Key Personnel
    • 14.2.5. Key Product/Services
  • 14.3. dotData Inc.
    • 14.3.1. Business Overview
    • 14.3.2. Key Revenue and Financials
    • 14.3.3. Recent Developments
    • 14.3.4. Key Personnel
    • 14.3.5. Key Product/Services
  • 14.4. IBM Corporation
    • 14.4.1. Business Overview
    • 14.4.2. Key Revenue and Financials
    • 14.4.3. Recent Developments
    • 14.4.4. Key Personnel
    • 14.4.5. Key Product/Services
  • 14.5. Dataiku
    • 14.5.1. Business Overview
    • 14.5.2. Key Revenue and Financials
    • 14.5.3. Recent Developments
    • 14.5.4. Key Personnel
    • 14.5.5. Key Product/Services
  • 14.6. EdgeVerve Systems Limited
    • 14.6.1. Business Overview
    • 14.6.2. Key Revenue and Financials
    • 14.6.3. Recent Developments
    • 14.6.4. Key Personnel
    • 14.6.5. Key Product/Services
  • 14.7. Big Squid Inc.
    • 14.7.1. Business Overview
    • 14.7.2. Key Revenue and Financials
    • 14.7.3. Recent Developments
    • 14.7.4. Key Personnel
    • 14.7.5. Key Product/Services
  • 14.8. SAS Institute Inc.
    • 14.8.1. Business Overview
    • 14.8.2. Key Revenue and Financials
    • 14.8.3. Recent Developments
    • 14.8.4. Key Personnel
    • 14.8.5. Key Product/Services
  • 14.9. Microsoft Corporation
    • 14.9.1. Business Overview
    • 14.9.2. Key Revenue and Financials
    • 14.9.3. Recent Developments
    • 14.9.4. Key Personnel
    • 14.9.5. Key Product/Services
  • 14.10. Determined.ai Inc
    • 14.10.1. Business Overview
    • 14.10.2. Key Revenue and Financials
    • 14.10.3. Recent Developments
    • 14.10.4. Key Personnel
    • 14.10.5. Key Product/Services

15. Strategic Recommendations

16. About Us & Disclaimer