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1370876

自動化機器學習解決方案市場 - 2018-2028 年全球產業規模、佔有率、趨勢、機會和預測，按產品、部署、自動化類型、企業規模、最終用戶、地區和競爭進行細分

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個工作天內

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簡介目錄

預計全球自動化機器學習解決方案市場將在 2023-2028 年預測期內蓬勃發展。使用預測線索評分系統進行客戶細分和瞄準潛在消費者正在增加全球對自動化機器學習 (AutoML) 解決方案的需求。

該行業的許多領域現在嚴重依賴機器學習 (ML)。另一方面，開發高性能機器學習系統需要高度專業化的資料科學家和主題專家。透過使領域專家能夠自動創建機器學習應用程式，而無需大量的統計和機器學習技能，自動化機器學習 (AutoML) 旨在減少對資料科學家的需求。資料科學和人工智慧的進步提高了自動化機器學習的性能。由於企業看到了這項技術的前景，因此其採用率預計在預估期間內將會增加。客戶現在可以更輕鬆地使用自動化機器學習解決方案，因為企業將其作為訂閱服務出售。此外，它還提供按需付費的靈活性。

最近，機器學習 (ML) 在各種應用中得到越來越多的使用，但沒有足夠的機器學習專業人員來跟上這種成長。自動化機器學習 (AutoML) 的目標是讓機器學習變得更平易近人。因此，專業人士應該能夠安裝更多的機器學習系統，並且使用 AutoML 比直接使用 ML 需要更少的技能。然而，該技術目前的接受程度還不夠，這限制了全球自動化機器學習解決方案市場的擴張。

市場概況
預測期 2024-2028
2022 年市場規模 11.2億美元
2028 年市場規模 93.4億美元
2023-2028 年年複合成長率 42.48%
成長最快的細分市場 製造業
最大的市場 北美洲

COVID-19 疫情之後，組織越來越依賴智慧解決方案來實現業務營運自動化，這導致人工智慧的使用增加。預計這種模式將在接下來的幾年中持續存在，從而加速人工智慧在業務營運中的採用。

對高效詐欺檢測解決方案的需求不斷成長

機器學習廣泛應用於金融應用，包括交易、流程自動化、信用評分以及貸款和保險承保。金融安全的主要問題之一是金融詐欺。機器學習目前正用於詐欺偵測應用，以應對日益嚴重的金融詐欺危險。為了利用最近獲得的數位管道獲取的大量資料，金融服務領域的幾家公司現在正在積極將人工智慧和機器學習整合到其生態系統中。疫情帶來的客戶行為和優先事項的範式變化也促進了其擴張，導致 54% 的員工人數超過 5,000 人的金融服務公司將技術整合到其業務實踐中。企業越來越需要一種詐騙偵測系統，該系統可以在接受線上信用卡付款時提供即時且可操作的警告。這些因素正在推動全球自動化機器學習解決方案市場的發展。

對智慧業務流程的需求正在上升

隨著企業現在轉向利用下一代技術，人工智慧 (AI) 的使用正在增加。企業可以將人工智慧用於多種目的，包括資料收集和工作流程效率。由於人工智慧分析在現成的 CRM 平台中廣泛使用，銷售團隊現在可以按需提供富有洞察力的資料。例如，Salesforce 的 Einstein AI 技術可以預測哪些客戶最有可能增加銷售並更換品牌。有了這樣的訊息，銷售人員就可以將時間和精力集中在最重要的地方。此外，企業越來越重視評估和改進客戶服務，這促進了組織內基於人工智慧的流程的擴展。它使企業能夠更好地了解消費者偏好和購買趨勢，從而使他們能夠提供量身定做的產品建議。由於機器人技術在包括製造和倉儲等在內的各個行業中不斷擴大部署，對人工智慧的需求正在增加。透過機器視覺等人工智慧技術，協作機器人能夠了解周遭的人。他們可以做出適當的反應，例如放慢速度或轉身避開人群。因此，可以創建流程來最大限度地發揮人和機器人的能力。

自動化機器學習工具的採用緩慢

機器學習 (ML) 正在越來越多的應用中使用，但沒有足夠的機器學習專家來跟上這種擴充功能。自動化機器學習 (AutoML) 的目標是讓機器學習變得更平易近人。因此，專家應該能夠安裝更多的機器學習系統，並且使用 AutoML 所需的技能比直接處理 ML 所需的技能要少。然而，目前該技術的接受度還不夠高，這限制了自動化機器學習解決方案市場的擴張。首先，有一種誤解，認為 AutoML 方法很難使用，並且需要大量的初始投資才能了解如何使用它們。其次，AutoML 系統偶爾會在處理使用者資料時遇到問題，但並不總是能識別問題。人們也擔心使用 AutoML 所需的處理能力。

不斷成長的醫療保健應用

醫療保健領域的許多應用已經利用了機器學習技術。該平台分析該垂直行業的數百萬個不同資料點，預測結果，並提供快速風險評估和精確的資源分配。

使用者對自動化機器學習解決方案的抵制

市場延遲採用自動化機器學習解決方案主要是由於機器學習技術的採用有限。公司很難獲得他們所需的領域專家，因為對機器學習適當能力的需求很大。此外，由於聘用這些專業人員的成本很高，企業更不可能採用機器學習等尖端技術。最終使用者的類型也可能會影響對使用 AutoML 技術的抵制。例如，考慮到政府組織管理公民資料，他們可能會抵制使用自動化機器學習解決方案。因此，對隱私和資料敏感度的擔憂可能會阻止他們使用此類解決方案，從而減緩市場的擴張。此外，由於技術的限制，人們不願意使用此類工具，一些行業專業人士已經注意到這一點。這些都是 AutoML 遇到的資料和模型應用問題。例如，離線資料處理過程中資料不一致、標記資料品質不夠高等都會產生負面影響。此外，團隊必須對非結構化和半結構化資料進行技術要求很高的自動化機器學習處理。

市場區隔

自動化機器學習解決方案市場分為產品、部署、自動化類型、企業規模、最終用戶、公司和地區。依產品提供，市場分為平台與服務。根據部署，市場分為本地和雲端。根據自動化類型，市場分為資料處理、特徵工程、建模和視覺化。根據企業規模，市場分為大型企業和中小企業。根據最終用戶，市場分為 BFSI、零售和電子商務、醫​​療保健和製造業。按地區分類，市場分為北美、亞太地區、歐洲、南美、中東和非洲

市場參與者

全球自動化機器學習解決方案市場的一些主要市場參與者包括 Datarobot Inc.、Amazon Web Services Inc.、dotData Inc.、IBM Corporation、Dataiku、EdgeVerve Systems Limited、Big Squid Inc.、SAS Institute Inc.、微軟公司、 Determine.ai Inc.

報告範圍：

在本報告中，除了下面詳細介紹的產業趨勢外，全球自動化機器學習解決方案市場還分為以下幾類：

自動化機器學習解決方案市場，透過提供

  • 平台
  • 服務

自動化機器學習解決方案市場（按部署）：

  • 本地部署
  • 雲

自動化機器學習解決方案市場（按自動化類型）：

  • 資料處理
  • 特徵工程
  • 造型
  • 視覺化

自動化機器學習解決方案市場，依企業規模分類：

  • 大型企業
  • 中小企業

自動化機器學習解決方案市場，按最終用戶分類：

  • BFSI
  • 零售與電子商務
  • 衛生保健
  • 製造業

自動化機器學習解決方案市場（按地區）：

  • 北美洲
  • 美國
  • 加拿大
  • 墨西哥
  • 亞太
  • 印度
  • 中國
  • 日本
  • 韓國
  • 澳洲
  • 新加坡
  • 馬來西亞
  • 歐洲
  • 德國
  • 英國
  • 法國
  • 俄羅斯
  • 西班牙
  • 比利時
  • 義大利
  • 南美洲
  • 巴西
  • 阿根廷
  • 哥倫比亞
  • 秘魯
  • 智利
  • 中東
  • 沙烏地阿拉伯
  • 南非
  • 阿拉伯聯合大公國
  • 以色列
  • 土耳其

競爭格局

  • 公司簡介：詳細分析全球自動化機器學習解決方案市場中的主要公司。

可用的客製化：

  • 全球自動化機器學習解決方案市場報告以及給定的市場資料，Tech Sci Research 根據公司的具體需求提供客製化服務。該報告可以使用以下自訂選項：

公司資訊

  • 其他市場參與者（最多五個）的詳細分析和概況分析。

目錄

第 1 章：服務概述

第 2 章：研究方法

第 3 章：COVID-19 對全球自動化機器學習解決方案市場的影響

第 4 章：執行摘要

第 5 章：客戶之聲

第 6 章：全球自動化機器學習解決方案市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 按產品提供（平台、服務）
    • 按部署（本地、雲端）
    • 依自動化類型（資料處理、特徵工程、建模、視覺化）
    • 依企業規模（大型企業、中小企業）
    • 按最終用戶（BFSI、零售和電子商務、醫​​療保健、製造業）
    • 按地區
  • 按公司分類 (2022)
  • 市場地圖

第 7 章：北美自動化機器學習解決方案市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 透過提供
    • 按部署
    • 按自動化類型
    • 按企業規模
    • 由最終用戶
    • 按國家/地區
  • 北美：國家分析
    • 美國
    • 加拿大
    • 墨西哥

第 8 章：亞太地區自動化機器學習解決方案市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 透過提供
    • 按部署
    • 按自動化類型
    • 按企業規模
    • 由最終用戶
    • 按國家/地區
  • 亞太地區：國家分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲
    • 新加坡
    • 馬來西亞

第 9 章：歐洲自動化機器學習解決方案市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 透過提供
    • 按部署
    • 按自動化類型
    • 按企業規模
    • 由最終用戶
    • 按國家/地區
  • 歐洲：國家分析
    • 德國
    • 英國
    • 法國
    • 俄羅斯
    • 西班牙
    • 比利時
    • 義大利

第 10 章：南美洲自動化機器學習解決方案市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 透過提供
    • 按部署
    • 按自動化類型
    • 按企業規模
    • 由最終用戶
    • 按國家/地區
  • 南美洲：國家分析
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 秘魯
    • 智利

第 11 章：中東和非洲自動化機器學習解決方案市場展望

  • 市場規模及預測
    • 按價值
  • 市佔率及預測
    • 透過提供
    • 按部署
    • 按自動化類型
    • 按企業規模
    • 由最終用戶
    • 按國家/地區
  • 中東和非洲：國家分析
    • 沙烏地阿拉伯
    • 南非
    • 阿拉伯聯合大公國
    • 以色列
    • 土耳其

第 12 章：市場動態

  • 促進要素
  • 挑戰

第 13 章：市場趨勢與發展

第 14 章：公司簡介

  • 數據機器人公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 亞馬遜網路服務公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 點數據公司
    • 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
  • 達泰庫
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • EdgeVerve系統有限公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 大魷魚公司
    • 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
  • 微軟公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services
  • 確定.ai公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel
    • Key Product/Services

第 15 章：策略建議

第 16 章：關於我們與免責聲明

簡介目錄
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