Global Deep Learning Market Size study & Forecast, by Solution, by Hardware by Application, by End Use and Regional Analysis, 2022-2029, 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 Deep Learning 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, Deep Learning market size forecast, market data & Graphs and Statistics, Tables, Bar &Pie Charts, and many more for business intelligence. Get the whole report, which includes a chart and more than 100 tables and figures. – Comprehensive Analysis of COVID-19 Market Outbreak Impact and Regional Situation
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Global Deep Learning Market is valued approximately at USD 37.15billion in 2021 and is anticipated to grow with a healthy growth rate of more than 33.5% over the forecast period 2022-2029. A sequence of computer instructions or algorithms known as “deep learning” are based on the structure and operation of the brain. It is a branch of machine learning. Deep learning is a method for teaching computers to learn by doing. Deep learning is frequently referred to as artificial neural networks or deep neural networks. Statistics and predictive modelling are also important components of data science, which also includes deep learning. The Deep Learning market is expanding because of factors such as increased penetration in big data analytics, improvement in deep learning algorithms and rising investment for the development of AI and ML However, requirement of large training datasets for recognition and high capital investment may halt market growth.
According to Statista, in year 2018 Volume of data/information created, captured, copied, and consumed worldwide stood at 33 zettabytes which increased to 79 zettabytes in year 2021 and it is projected to reach at 181 zettabytes by year 2025. Thus, rise in generation of data volume across the world is fostering market growth. Thus rising data volume generation across the world is catering the market growth. Along with these, the market is growing rapidly due to the widespread adoption of connected devices in educational institutions and government measures to enhance industry vertical digitalization. For instance, the Australian Catholic University (ACU) created a data lake in July 2020 using its newly combined data environment to offer a unified view of student progress. In order to assist students who might require further support or who run the risk of quitting the university altogether, it makes use of Microsoft’s Power BI and Azure data platform. As a result, this is seen as a significant component promoting market expansion. In addition, increasing adoption of cloud-based technology across several industries. However, the high cost of Deep Learning stifles market growth throughout the forecast period of 2022-2029.
The key regions considered for the Global Deep Learning Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the market in terms of revenue, owing to rising investment in artificial intelligence, rise in adoption of image and pattern recognition technology. Whereas, Europe is expected to grow with a highest CAGR during the forecast period, owing to factors such as rising government initiatives to adopt artificial intelligence and machine learning in various end use industry.
Major market player included in this report are:
- Advanced Micro Devices, Inc.
- ARM Ltd.
- Clarifai, Inc.
- Entilic
- Google, Inc.
- HyperVerge
- IBM Corporation
- Intel Corporation
- Microsoft Corporation
- NVIDIA Corporation
Recent Developments in the Market:
In June 2020, Facebook AI Research announced the launch of TransCoder. It is a system which utilizes unsupervised deep-learning in conversion of code from one programming language to the another.
In May 2020, IBM announced that it would use a variety of artificial intelligence (AI) technologies to automate the management of IT operations and modernise applications. It employs machine learning and deep learning algorithms to time series data, semi-structured logs, structured data, and unstructured data spanning IT issues and human dialogues to trace the history of a problem.
Global Deep Learning Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Solution, Hardware, Application, End use, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*
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 years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.
The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Solution offerings of key players. The detailed segments and sub-segment of the market are explained below.
By Solution:
- Hardware
- Software
- Services
By Hardware:
- Central Processing Unit (CPU)
- Graphics Processing Unit (GPU)
- Field Programmable Gate Array (FPGA)
- Application-Specific Integration Circuit (ASIC)
By Application:
- Image recognition
- Voice recognition
- Video surveillance & diagnostics
- Data mining
By End Use:
- Automotive
- Aerospace & Defense
- Healthcare
- Retail
- Others
By Region:
- North America
- U.S.
- Canada
- Europe
- UK
- Germany
- France
- Spain
- Italy
- ROE
- Asia Pacific
- China
- India
- Japan
- Australia
- South Korea
- RoAPAC
- Latin America
- Brazil
- Mexico
- RoLA
- Rest of the World
What our report offers:
- Executive Summary: A concise overview of the report, highlighting the main points, key findings, and recommendations.
- Introduction: Sets the context for the report by explaining the purpose, scope, and objectives. It may also include background information on the topic.
- Methodology: Describes the methods and approaches used to gather data, conduct research, and analyze information for the report. This section provides transparency and credibility to the findings.
- Findings/Results: Presents the main information, data, and analysis related to the topic. It may include charts, graphs, tables, or other visual aids to support the findings.
- Analysis and Interpretation: Provides an in-depth examination and interpretation of the findings. It may involve comparing data, identifying trends, and drawing conclusions based on the evidence presented.
- Discussion: Explores the implications and significance of the findings within the broader context. This section may address challenges, opportunities, and potential solutions related to the subject matter.
- Recommendations: Offers actionable suggestions based on the analysis and findings of the report. Recommendations should be specific, feasible, and linked to the report’s objectives.
- References/Citations: Includes a list of sources, references, or citations used in the report. This ensures proper attribution and allows readers to explore the referenced material.
- Appendices: Supplementary materials such as additional data, charts, or supporting documents that are relevant to the report but not included in the main body.
- Conclusion: Summarizes the key points discussed in the report and reinforces the main findings.
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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.
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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- What are the key drivers influencing market growth?
- What are the major challenges or constraints faced by market participants?
- What are the emerging trends and opportunities in the market?
- Who are the major competitors in the market and what is their market share?
- What are the key customer segments and their preferences within the market?
- What are the regional or geographic trends and variations within the market?
- What are the regulatory and legal factors impacting the market?
- What are the technological advancements or innovations shaping the market?
- What are the pricing trends and strategies observed in the market?
- What are the distribution channels and their effectiveness in reaching the target market?
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Key Points Covered in Deep Learning Market Report:
Table of Contents
Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Deep Learning Market, by Region, 2019-2029 (USD Billion)
1.2.2. Deep Learning Market, by Solution, 2019-2029 (USD Billion)
1.2.3. Deep Learning Market, by Hardware, 2019-2029 (USD Billion)
1.2.4. Deep Learning Market, by Application, 2019-2029 (USD Billion)
1.2.5. Deep Learning Market, by End Use, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Deep Learning Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Deep Learning Market Dynamics
3.1. Deep Learning Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increased penetration in big data analytics
3.1.1.2. Improvement in deep learning algorithms
3.1.1.3. Rising investment for the development of AI and ML
3.1.2. Market Challenges
3.1.2.1. Requirement of large training datasets for recognition
3.1.2.2. High Capital Investment
3.1.3. Market Opportunities
3.1.3.1. Increasing adoption of cloud-based technology across several industries
Chapter 4. Global Deep Learning Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
……..and view more in complete table of Contents
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