Deep Learning Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028

Deep Learning Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028

The global deep learning market size reached US$ 17.2 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 113.0 Billion by 2028, exhibiting a growth rate (CAGR) of 38.2% during 2023-2028.

Deep learning, or deep structured learning, is a division of machine learning that uses layered algorithmic models for analyzing data. It is a crucial component of data science, which uses statistics and predictive modeling for collecting, analyzing and interpreting large amounts of information. It also involves the use of artificial intelligence (AI) to imitate the functioning of the human brain while processing data, forming patterns and making decisions. This technology is commonly used in image recognition tools, natural language processing (NLP) and speech recognition software, self-driving vehicles and language translation services and finds extensive applications across the retail, healthcare, automotive, agriculture, security and manufacturing industries.

The expanding information technology (IT) industry, along with the rising trend of digitalization, is one of the key factors driving the growth of the market. In comparison to the traditionally used computing systems, deep learning algorithms can automatically intercept available data points, which enhances the efficiency and accuracy of the decision-making process. Furthermore, deep learning solutions are widely employed for cybersecurity, database management and fraud detection systems. They are also utilized for processing medical images for disease diagnosis and drug discovery and offering virtual patient assistance in the healthcare sector, which is contributing to the widespread adoption of the technology. Other factors, including its integration with big data analytics and cloud computing, along with extensive research and development (R&D) activities to develop improved hardware and software processing solutions for deep learning, are projected to drive the market in the coming years.

Key Market Segmentation:
IMARC Group provides an analysis of the key trends in each sub-segment of the global deep learning market report, along with forecasts at the global, regional and country level from 2023-2028. Our report has categorized the market based on product type, application, end-use industry and architecture.

Breakup by Product Type:

Software
Services
Hardware

Breakup by Application:

Image Recognition
Signal Recognition
Data Mining
Others

Breakup by End-Use Industry:

Security
Manufacturing
Retail
Automotive
Healthcare
Agriculture
Others

Breakup by Architecture:

RNN
CNN
DBN
DSN
GRU

Breakup by Region:

North America
United States
Canada
Asia Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa

Competitive Landscape:
The report has also analysed the competitive landscape of the market with some of the key players being Amazon Web Services (AWS), Google Inc., IBM, Intel, Micron Technology, Microsoft Corporation, Nvidia, Qualcomm, Samsung Electronics, Sensory Inc., Pathmind, Inc., Xilinx, etc.

Key Questions Answered in This Report

1. What was the size of the global deep learning market in 2022?
2. What is the expected growth rate of the global deep learning market during 2023-2028?
3. What has been the impact of COVID-19 on the global deep learning market?
4. What are the key factors driving the global deep learning market?
5. What is the breakup of the global deep learning market based on the product type?
6. What is the breakup of the global deep learning market based on the application?
7. What is the breakup of the global deep learning market based on the end-use industry?
8. What are the key regions in the global deep learning market?
9. Who are the key players/companies in the global deep learning market?


1 Preface
2 Scope and Methodology
2.1 Objectives of the Study
2.2 Stakeholders
2.3 Data Sources
2.3.1 Primary Sources
2.3.2 Secondary Sources
2.4 Market Estimation
2.4.1 Bottom-Up Approach
2.4.2 Top-Down Approach
2.5 Forecasting Methodology
3 Executive Summary
4 Introduction
4.1 Overview
4.2 Key Industry Trends
5 Global Deep Learning Market
5.1 Market Overview
5.2 Market Performance
5.3 Impact of COVID-19
5.4 Market Forecast
6 Market Breakup by Product Type
6.1 Software
6.1.1 Market Trends
6.1.2 Market Forecast
6.2 Services
6.2.1 Market Trends
6.2.2 Market Forecast
6.3 Hardware
6.3.1 Market Trends
6.3.2 Market Forecast
7 Market Breakup by Application
7.1 Image Recognition
7.1.1 Market Trends
7.1.2 Market Forecast
7.2 Signal Recognition
7.2.1 Market Trends
7.2.2 Market Forecast
7.3 Data Mining
7.3.1 Market Trends
7.3.2 Market Forecast
7.4 Others
7.4.1 Market Trends
7.4.2 Market Forecast
8 Market Breakup by End-Use Industry
8.1 Security
8.1.1 Market Trends
8.1.2 Market Forecast
8.2 Manufacturing
8.2.1 Market Trends
8.2.2 Market Forecast
8.3 Retail
8.3.1 Market Trends
8.3.2 Market Forecast
8.4 Automotive
8.4.1 Market Trends
8.4.2 Market Forecast
8.5 Healthcare
8.5.1 Market Trends
8.5.2 Market Forecast
8.6 Agriculture
8.6.1 Market Trends
8.6.2 Market Forecast
8.7 Others
8.7.1 Market Trends
8.7.2 Market Forecast
9 Market Breakup by Architecture
9.1 RNN
9.1.1 Market Trends
9.1.2 Market Forecast
9.2 CNN
9.2.1 Market Trends
9.2.2 Market Forecast
9.3 DBN
9.3.1 Market Trends
9.3.2 Market Forecast
9.4 DSN
9.4.1 Market Trends
9.4.2 Market Forecast
9.5 GRU
9.5.1 Market Trends
9.5.2 Market Forecast
10 Market Breakup by Region
10.1 North America
10.1.1 United States
10.1.1.1 Market Trends
10.1.1.2 Market Forecast
10.1.2 Canada
10.1.2.1 Market Trends
10.1.2.2 Market Forecast
10.2 Asia Pacific
10.2.1 China
10.2.1.1 Market Trends
10.2.1.2 Market Forecast
10.2.2 Japan
10.2.2.1 Market Trends
10.2.2.2 Market Forecast
10.2.3 India
10.2.3.1 Market Trends
10.2.3.2 Market Forecast
10.2.4 South Korea
10.2.4.1 Market Trends
10.2.4.2 Market Forecast
10.2.5 Australia
10.2.5.1 Market Trends
10.2.5.2 Market Forecast
10.2.6 Indonesia
10.2.6.1 Market Trends
10.2.6.2 Market Forecast
10.2.7 Others
10.2.7.1 Market Trends
10.2.7.2 Market Forecast
10.3 Europe
10.3.1 Germany
10.3.1.1 Market Trends
10.3.1.2 Market Forecast
10.3.2 France
10.3.2.1 Market Trends
10.3.2.2 Market Forecast
10.3.3 United Kingdom
10.3.3.1 Market Trends
10.3.3.2 Market Forecast
10.3.4 Italy
10.3.4.1 Market Trends
10.3.4.2 Market Forecast
10.3.5 Spain
10.3.5.1 Market Trends
10.3.5.2 Market Forecast
10.3.6 Russia
10.3.6.1 Market Trends
10.3.6.2 Market Forecast
10.3.7 Others
10.3.7.1 Market Trends
10.3.7.2 Market Forecast
10.4 Latin America
10.4.1 Brazil
10.4.1.1 Market Trends
10.4.1.2 Market Forecast
10.4.2 Mexico
10.4.2.1 Market Trends
10.4.2.2 Market Forecast
10.4.3 Others
10.4.3.1 Market Trends
10.4.3.2 Market Forecast
10.5 Middle East and Africa
10.5.1 Market Trends
10.5.2 Market Breakup by Country
10.5.3 Market Forecast
11 SWOT Analysis
11.1 Overview
11.2 Strengths
11.3 Weaknesses
11.4 Opportunities
11.5 Threats
12 Value Chain Analysis
13 Porters Five Forces Analysis
13.1 Overview
13.2 Bargaining Power of Buyers
13.3 Bargaining Power of Suppliers
13.4 Degree of Competition
13.5 Threat of New Entrants
13.6 Threat of Substitutes
14 Competitive Landscape
14.1 Market Structure
14.2 Key Players
14.3 Profiles of Key Players
14.3.1 Amazon Web Services (AWS)
14.3.1.1 Company Overview
14.3.1.2 Product Portfolio
14.3.2 Google Inc.
14.3.2.1 Company Overview
14.3.2.2 Product Portfolio
14.3.2.3 SWOT Analysis
14.3.3 IBM
14.3.3.1 Company Overview
14.3.3.2 Product Portfolio
14.3.4 Intel
14.3.4.1 Company Overview
14.3.4.2 Product Portfolio
14.3.4.3 Financials
14.3.4.4 SWOT Analysis
14.3.5 Micron Technology
14.3.5.1 Company Overview
14.3.5.2 Product Portfolio
14.3.5.3 Financials
14.3.5.4 SWOT Analysis
14.3.6 Microsoft Corporation
14.3.6.1 Company Overview
14.3.6.2 Product Portfolio
14.3.6.3 Financials
14.3.6.4 SWOT Analysis
14.3.7 Nvidia
14.3.7.1 Company Overview
14.3.7.2 Product Portfolio
14.3.7.3 Financials
14.3.7.4 SWOT Analysis
14.3.8 Qualcomm
14.3.8.1 Company Overview
14.3.8.2 Product Portfolio
14.3.8.3 Financials
14.3.8.4 SWOT Analysis
14.3.9 Samsung Electronics
14.3.9.1 Company Overview
14.3.9.2 Product Portfolio
14.3.10 Sensory Inc.
14.3.10.1 Company Overview
14.3.10.2 Product Portfolio
14.3.11 Pathmind Inc.
14.3.11.1 Company Overview
14.3.11.2 Product Portfolio
14.3.12 Xilinx
14.3.12.1 Company Overview
14.3.12.2 Product Portfolio
14.3.12.3 Financials
14.3.12.4 SWOT Analysis

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