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Machine Learning as a Service-Global Market Trends, Drivers, Strategies, Applications and Competitive Landscape 2023

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Machine Learning as a Service (MLaaS) market is expected to grow from $ 679.32 million in 2016 to reach $ 7620.18 million by 2023 with a CAGR of 41.2%. Rising investments in the healthcare business, emerging multiple options in application areas, enhanced connectivity and enlargement in data from IoT platforms are the current trends in machine learning as a service market. Strong need to recognize consumer behaviour, acceptance of cloud-based technologies, and advancements in technologies are some of the major factors enhancing the market growth. However, the lack of trained consultants to organize machine learning services and government & compliance issues are restraining the growth of MLaaS solutions market.

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On the basis of organization, small and medium businesses segment is projected to adopt machine learning service. With the help of predictive analytics machine learning, algorithms not only give real-time data but also predict the future. Machine learning solutions are used by small and medium businesses for fine-tuning their supply chain by forecasting the demand of a product and by suggesting the timing and quantity of supplies essential for satisfying the customers’ expectations.

North America is expected to capture significant growth during forecast period. High adoption rate of new technologies and huge demand for technologies like machine learning and big data are expected to drive the machine learning market in this region.

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Table of Content: 

1 Executive Summary 

2 Preface 
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions

3 Market Trend Analysis 
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Application Analysis
3.7 End User Analysis
3.8 Emerging Markets
3.9 Futuristic Market Scenario

4 Porters Five Force Analysis 
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry

5 Global Machine Learning as a Service (MLaaS) Market, By Application 
5.1 Introduction
5.2 Network Analytics and Automated Traffic Management
5.3 Augmented Reality
5.4 Predictive Maintenance
5.5 Fraud Detection and Risk Analytics
5.6 Marketing and Advertising
5.7 Other Applications

6 Global Machine Learning as a Service (MLaaS) Market, By End User 
6.1 Introduction
6.2 Education
6.3 Automotive and Transportation
6.4 Telecom
6.5 Banking and Financial Services
6.6 Retail and E-Commerce
6.7 Media and Entertainment
6.8 Insurance
6.9 Healthcare
6.10 Defense
6.11 Other End Users

7 Global Machine Learning as a Service (MLaaS) Market, By Component 
7.1 Introduction
7.2 Services
7.2.1 Managed Services
7.2.2 Professional Services
7.3 Software Tools
7.3.1 Modeler and Processing
7.3.2 Data Storage and Archiving
7.3.3 Cloud and Web-Based Application Programming Interface
7.3.4 Other Software Tools

Also Read:  Automotive Telematics-Global Market Outlook 2017-2023

8 Global Machine Learning as a Service (MLaaS) Market, By Organization Size 
8.1 Introduction
8.2 Small and Medium Enterprises
8.3 Large Enterprises

9 Global Machine Learning as a Service (MLaaS) Market, By Geography 
9.1 Introduction
9.2 North America
9.2.1 US
9.2.2 Canada
9.2.3 Mexico
9.3 Europe
9.3.1 Germany
9.3.2 UK
9.3.3 Italy
9.3.4 France
9.3.5 Spain
9.3.6 Rest of Europe
9.4 Asia Pacific
9.4.1 Japan
9.4.2 China
9.4.3 India
9.4.4 Australia
9.4.5 New Zealand
9.4.6 South Korea
9.4.7 Rest of Asia Pacific
9.5 South America
9.5.1 Argentina
9.5.2 Brazil
9.5.3 Chile
9.5.4 Rest of South America
9.6 Middle East & Africa
9.6.1 Saudi Arabia
9.6.2 UAE
9.6.3 Qatar
9.6.4 South Africa
9.6.5 Rest of Middle East & Africa

10 Key Developments 
10.1 Agreements, Partnerships, Collaborations and Joint Ventures
10.2 Acquisitions & Mergers
10.3 New Product Launch
10.4 Expansions
10.5 Other Key Strategies

11 Company Profiling 
11.1 Microsoft
11.2 AT&T
11.3 FICO
11.4 Ersatz Labs, Inc.
11.5 International Business Machine Corporation
11.6 Fuzzy.Ai
11.7 Amazon Web Services
11.8 Hewlett-Packard Enterprise Development Lp.
11.9 Google, Inc.
11.10 Yottamine Analytics, LLC
11.11 Sift Science, Inc.
11.12 BigML, Inc.
11.13 iCarbonX

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