Machine Learning As A Service Market Key Player Analysis By Google Inc., SAS Institute Inc., FICO, Hewlett Packard Enterprise, Yottamine Analytics, Amazon Web Services, BigML, Inc., Microsoft Corporation, Predictron Labs Ltd., and IBM Corporation.

The report is a comprehensive exploration of global Machine Learning As A Service market offering growth rates, size of the industry, competitive landscape information, factors to the contributing growth of the global Machine Learning As A Service market and more.

Machine Learning As A Service market is a process of data analysis that comprises of statistical data analysis performed to derive desired predictive output without the implementation of explicit programming. It is designed to incorporate the functionalities of artificial intelligence (AI) and cognitive computing involving a series of algorithms and is used to understand the relationship between datasets to obtain a desired output. Machine learning as a service (MLaaS) incorporates range of services that offer machine learning tools through cloud computing services. The global machine learning as a service market was valued at $571 million in 2016, and is projected to reach $5,537 million by 2023, growing at a CAGR of 39.0% from 2017 to 2023.

Increased penetration of cloud-based solutions, growth associated with artificial intelligence and cognitive computing market, and increase in market for prediction solutions drive the market growth. In addition, growth in IT expenditure in emerging nations and technological advancements for workflow optimization fuel the demand for advanced analytical systems driving the machine learning as a service market growth. However, dearth of trained professionals is expected to impede the machine learning as a service market share. Furthermore, increased application areas and growth of IoT is expected to create lucrative opportunities for machine learning as a service market growth.

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The global machine learning as a service market is segmented based on component, organization size, end-use industry, application, and geography. The component segment is bifurcated into software and services. Based on organization size, it is divided into large enterprises and small & medium enterprises. The application segment is categorized into marketing & advertising, fraud detection & risk management, predictive analytics, augmented & virtual reality, natural language processing, computer vision, security & surveillance, and others. On the basis of end-use industry, it is classified into aerospace & defense, IT & telecom, energy & utilities, public sector, manufacturing, BFSI, healthcare, retail, and others. By geography, the machine learning as a service market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.

Key players that operate in the machine learning as a service market are Google Inc., SAS Institute Inc., FICO, Hewlett Packard Enterprise, Yottamine Analytics, Amazon Web Services, BigML, Inc., Microsoft Corporation, Predictron Labs Ltd., and IBM Corporation.

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KEY BENEFITS FOR STAKEHOLDERS

This report provides an overview of the trends, structure, drivers, challenges, and opportunities in the global machine learning as a service market.

Porter’s Five Forces analysis highlights the potential of buyers & suppliers, and provides insights on the competitive structure of the market to determine the investment pockets.

Current and future trends adopted by the key market players are highlighted to determine overall competitiveness.

The quantitative analysis of the machine learning as a service market growth from 2017 to 2023 is provided to elaborate the market potential.

By Component

Software

Services

By Organization Size

Large Enterprises

Small & Medium Enterprises

By End-Use Industry

Aerospace & Defence

IT & Telecom

Energy & Utilities

Public sector

Manufacturing

BFSI

Healthcare

Retail

Others

By Application

Marketing & Advertising

Fraud Detection & Risk Management

Predictive analytics

Augmented & Virtual reality

Natural Language processing

Computer vision

Security & surveillance

Others

Table of content:

CHAPTER 1: INTRODUCTION

1.1. Report description

1.2. Key benefits for stakeholders

1.3. Key market segment

1.4. Research methodology

1.4.1. Secondary research

1.4.2. Primary research

1.4.3. Analyst tools & models

CHAPTER 2: EXECUTIVE SUMMARY

2.1. CXO perspective

CHAPTER 3: MARKET OVERVIEW

3.1. Market definition and scope

3.2. Key findings

3.2.1. Top impacting factors

3.2.2. Top investment pockets

3.2.3. Top Winning Strategies

3.2.4. Top Winning Strategies, By Year, 2016-2018*

3.2.5. Top Winning Strategies, By Development, 2016-2018* (%)

3.2.6. Top Winning Strategies, By Company, 2016-2018*

3.3. Porter's five forces analysis

3.4. Market share, 2017

3.5. Market dynamics

3.5.1. Drivers

3.5.1.1. Rise in demand for enhanced user experience and convenience features

3.5.1.2. Growing demand of autonomous vehicle

3.5.2. Restraint

3.5.2.1. Rise security and privacy concerns

3.5.3. Opportunity

3.5.3.1. Increasing demand for premium vehicle segment

CHAPTER 4: MACHINE LEARNING AS A SERVICE MARKET, BY COMPONENT

4.1. Overview

4.2. Hardware

4.2.1. Key market trends and opportunities

4.2.2. Market size and forecast, by region

4.2.3. Market size and forecast, by hardware type

4.2.3.1 Processor

4.2.3.1.1. Market size and forecast, by processor

4.2.3.1.2. Microprocessor (MPU)

4.2.3.1.3. Graphics Processing Unit (GPU)

4.2.3.1 Memory

4.2.3.1 Network

4.2.4. Market analysis, by country

4.3. Software

4.3.1. Key market trends and opportunities

4.3.2. Market size and forecast, by region

4.3.3. Market analysis, by country

4.4. Services

4.4.1. Key market trends and opportunities

4.4.2. Market size and forecast, by region

4.4.3. Market analysis, by country

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