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Machine Learning as a Service Market Is Booming Worldwide | Google, IBM Corporation, Microsoft Corporation, Amazon Web Services

10-05-2020 09:36 AM CET | IT, New Media & Software

Press release from: Report Ocean

Machine Learning as a Service Market

Machine Learning as a Service Market

Machine Learning as a Service Market Size study, by Type (Software Tools, Cloud and Web-based Application Programming Interface (APIs), Others), by Application (Manufacturing, Retail, Healthcare & Life Sciences, Telecom, BFSI, Others (Energy & Utilities, Education, Government)) and Regional Forecasts 2025 , Covid 19 Outbreak Impact research report added by Report Ocean, is an in-depth analysis of 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. It places the market within the context of the wider Machine Learning as a Service market, and compares it with other markets., market definition, regional market opportunity, sales and revenue by region, manufacturing cost analysis, Industrial Chain, market effect factors analysis, Machine Learning as a Service market size forecast, market data & Graphs and Statistics, Tables, Bar &Pie Charts, and many more for business intelligence. Get complete Report (Including Full TOC, 100+ Tables & Figures, and Chart). - In-depth Analysis Pre & Post COVID-19 Market Outbreak Impact Analysis

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Machine Learning as a Service Market to reach USD 16.13 billion by 2025.

Machine Learning as a Service Market valued approximately USD 0.87 billion in 2017 is anticipated to grow with a healthy growth rate of more than 43.9% over the forecast period 2018-2025.

Machine learning as a service is a significant range of solutions and services that are offered by cloud service providers. The tools offered by service providers include APIs, data visualization, natural language processing, face recognition, deep learning, and predictive analytics. The main benefit associated with these services is that the customers are able to quickly start with machine learning with no need to install or download any software on their servers. Enhancements in technology, growth in data volume and rise in IT spending in some of the developing regions are the major factors which are driving the growth in the global market. Additionally, growth in acceptance of cloud-based technologies and increasing need to know customer behavior are further boosting the demand for Machine learning as a service. Moreover, the high demand for private cloud in enterprises is likely to propel the growth of the market. Besides this, a rise in the area of application and growing investments in the healthcare sector represents significant growth opportunities for the market in the near future. However, scarcity of trained expertise and several security concerns are expected to hamper the market growth.

The regional analysis of Machine Learning as a Service Market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America and Rest of the World. In region such as Asia-Pacific, Middle-East and Africa, rise in usage of passenger vehicles set the growth in Machine Learning as a Service Market over the forecasted period 2018-2025. Asia-Pacific is estimated to hold a prominent share of the Machine Learning as a Service market. Developing countries, such as India and China, are significant players boosting the demand for the Machine Learning as a Service Market. Europe, North America and the Middle East and Africa are continuously witnessing infrastructural growth which fueling the demand of Machine Learning as a Service Market over the coming years. Asia Pacific region is contributing towards the growth of global Machine Learning as a Service Market and anticipated to exhibit higher growth rate / CAGR over the forecast period 2018-2025.

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Type:

 Software Tools
 Cloud and Web-based Application Programming Interface (APIs)
 Others

By Application:

 Manufacturing
 Retail
 Healthcare & Life Sciences
 Telecom
 BFSI
 Others (Energy & Utilities, Education, Government)
The leading Market players mainly include-
• Google
• IBM Corporation
• Microsoft Corporation
• Amazon Web Services
• BigML
• FICO
• Yottamine Analytics
• Ersatz Labs
• Predictron Labs
• H2O.ai
• AT&T
• Sift Science

A combination of factors, including COVID-19 containment situation, end-use market recovery & Recovery Timeline of 2020/ 2021
covid-19 scenario Market Behavior/ Level of Risk and Opportunity End Industry Behavior/ Opportunity Assessment Expected Industry Recovery Timeline Business Impact Horizon
Opening of Economy by Q3 2020 xx xx xx xx
Recovery – Opening of Economy extended till Q4 2020 / Q1 2021 xx xx xx xx

Geographical Breakdown: 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 impact and recovery path of Covid 19 for all regions, key developed countries and major emerging markets.

Countries: Argentina; Australia; Austria; Belgium; Brazil; Canada; Chile; China; Colombia; Czech Republic; Denmark; Egypt; Finland; France; Germany; Hong Kong; India; Indonesia; Ireland; Israel; Italy; Japan; Malaysia; Mexico; Netherlands; New Zealand; Nigeria; Norway; Peru; Philippines; Poland; Portugal; Romania; Russia; Saudi Arabia; Singapore; South Africa; South Korea; Spain; Sweden; Switzerland; Thailand; Turkey; UAE; UK; USA; Venezuela; Vietnam

In-Depth Qualitative COVID 19 Outbreak Impact Analysis Include Identification And Investigation Of The Following Aspects: Market Structure, Growth Drivers, Restraints and Challenges, Emerging Product Trends & Market Opportunities, Porter’s Fiver Forces. The report also inspects the financial standing of the leading companies, which includes gross profit, revenue generation, sales volume, sales revenue, manufacturing cost, individual growth rate, and other financial ratios. The report basically gives information about the Market trends, growth factors, limitations, opportunities, challenges, future forecasts, and details about all the key market players.

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Key questions answered: Study Explore COVID 19 Outbreak Impact Analysis

Q.1 What are some of the most promising potential, high growth opportunities for the global market by application, by product, by end user and by region (North America, Europe, Asia Pacific, and the Rest of the World)?
Q.2 Which segments will grow at a faster speed and why?
Q.3 Which regions will grow at a faster speed and why?
Q.4 What are the key factors affecting market dynamics? What are the drivers and challenges of the market?
Q.5 What are the business risks and threats of market?
Q.6 What are emerging trends in market and the reasons behind them?
Q.7 What are some changing demands of customers in the market?
Q.8 What are the new developments in the market? Which companies are leading these developments?
Q.9 Who are the leading players in market? What strategic initiatives are being implemented by key players for business growth?
Q.10 What are some of the competitive products and processes in this market?
Q.11 What M & A activities have taken place in the last five years in this market?

The Study Explore COVID 19 Outbreak Impact Analysis

• What should be entry strategies, countermeasures to economic impact, and marketing channels?
• What are market dynamics?
• What are challenges and opportunities?
• What is economic impact on market?
• What is current market status? What’s market competition in this industry, both company, and country wise? What’s market analysis by taking applications and types in consideration?

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Key Points Covered in Machine Learning as a Service Market Report:

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Key Trends
1.3. Global & Segmental Market Estimates & Forecasts, 2015-2025 (USD Billion)
1.3.1. Machine Learning as a Service, by Type, 2015-2025 (USD Billion)
1.3.2. Machine Learning as a Service, by Application, 2015-2025 (USD Billion)
1.3.3. Machine Learning as a Service, by Region, 2015-2025 (USD Billion)
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Machine Learning as a Service Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Machine Learning as a Service Market Dynamics
3.1. See Saw Analysis
3.1.1. Market Drivers
3.1.2. Market Challenges
3.1.3. Market Opportunities
Chapter 4. Machine Learning as a Service Market Industry Analysis
4.1. Porter's 5 Force Model
4.1.1. Bargaining Power of Buyers
4.1.2. Bargaining Power of Suppliers
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
4.2. PEST Analysis
4.2.1. Political Scenario
4.2.2. Economic Scenario
4.2.3. Social Scenario
4.2.4. Technological Scenario
4.3. Value Chain Analysis
4.3.1. Supplier
4.3.2. Manufacturers/Service Provider
4.3.3. Distributors
4.3.4. End-Users
4.4. Key Buying Criteria
4.5. Regulatory Framework
4.6. Cost Structure Analysis
4.6.1. Raw Material Cost Analysis
4.6.2. Manufacturing Cost Analysis
4.6.3. Labour Cost Analysis
4.7. Investment Vs Adoption Scenario
4.8. Analyst Recommendation & Conclusion

Chapter 5. Machine Learning as a Service, by Type
5.1. Market Snapshot
5.2. Market Performance - Potential Model
5.3. Key Market Players
5.4. Machine Learning as a Service, Sub Segment Analysis
5.4.1. Software Tools
5.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)
5.4.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)
5.4.2. Cloud and Web-based Application Programming Interface (APIs)
5.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)
5.4.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)
5.4.3. Others
5.4.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)
5.4.3.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 6. Machine Learning as a Service, by Application
6.1. Market Snapshot
6.2. Market Performance - Potential Model
6.3. Key Market Players
6.4. Machine Learning as a Service, Sub Segment Analysis
6.4.1. Manufacturing
6.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)
6.4.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)
6.4.2. Retail
6.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)
6.4.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)
6.4.3. Healthcare & Life Sciences
6.4.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)
6.4.3.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)
6.4.4. Telecom
6.4.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)
6.4.4.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)
6.4.5. BFSI
6.4.5.1. Market estimates & forecasts, 2015-2025 (USD Billion)
6.4.5.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)
6.4.6. Others (Energy & Utilities, Education, Government)
6.4.6.1. Market estimates & forecasts, 2015-2025 (USD Billion)
6.4.6.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 7. Machine Learning as a Service, by Regional Analysis
7.1. Machine Learning as a Service, Regional Market Snapshot (2015-2025)
7.2. North America Machine Learning as a Service Market Snapshot
7.2.1. U.S.
7.2.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.2.1.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.2.1.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.2.2. Canada
7.2.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.2.2.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.2.2.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.3. Europe Machine Learning as a Service Market Snapshot
7.3.1. U.K.
7.3.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.3.1.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.3.1.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.3.2. Germany
7.3.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.3.2.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.3.2.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.3.3. France
7.3.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.3.3.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.3.3.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.3.4. Rest of Europe
7.3.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.3.4.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.3.4.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.4. Asia Machine Learning as a Service Market Snapshot
7.4.1. China
7.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.4.1.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.4.1.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.4.2. India
7.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.4.2.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.4.2.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.4.3. Japan
7.4.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.4.3.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.4.3.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.4.4. Rest of Asia Pacific
7.4.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.4.4.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.4.4.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.5. Latin America Machine Learning as a Service Market Snapshot
7.5.1. Brazil
7.5.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.5.1.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.5.1.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.5.2. Mexico
7.5.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.5.2.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.5.2.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.6. Rest of The World
7.6.1. South America
7.6.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.6.1.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.6.1.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.6.2. Middle East and Africa
7.6.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)
7.6.2.2. Type breakdown estimates & forecasts, 2015-2025 (USD Billion)
7.6.2.3. Application breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 8. Competitive Intelligence
8.1. Company Market Share (Subject to Data Availability)
8.2. Top Market Strategies
8.3. Company Profiles
8.3.1. Google
8.3.1.1. Overview
8.3.1.2. Financial (Subject to Data Availability)
8.3.1.3. Product Summary
8.3.1.4. Recent Developments
8.3.2. IBM Corporation
8.3.3. Microsoft Corporation
8.3.4. Amazon Web Services
8.3.5. BigML
8.3.6. FICO
8.3.7. Yottamine Analytics
8.3.8. Ersatz Labs
8.3.9. Predictron Labs
8.3.10. H2O.ai
8.3.11. AT&T
8.3.12. Sift Science

Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.1.6. Research Assumption

TABLE 1. LIST OF SECONDARY SOURCES, USED IN THE STUDY OF MACHINE LEARNING AS A SERVICE
TABLE 2. LIST OF PRIMARY SOURCES, USED IN THE STUDY OF MACHINE LEARNING AS A SERVICE
TABLE 3. MACHINE LEARNING AS A SERVICE, REPORT SCOPE
TABLE 4. YEARS CONSIDERED FOR THE STUDY
……..and view more in complete table of Contents

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