Sale!

Global Deep Learning Market (2018-2023)

$3,999 $2,799

Global Deep Learning Market

In enterprise computing, deep learning is evolving into one of the most advanced technologies. Deep learning is a subset of machine learning in Artificial Intelligence (AI) that has networks capable of learning unsupervi

Description

Global Deep Learning Market

In enterprise computing, deep learning is evolving into one of the most advanced technologies. Deep learning is a subset of machine learning in Artificial Intelligence (AI) that has networks capable of learning unsupervised, from data that is unstructured or unlabeled.
By offering expert assistance, it would be able to assist humans in extending their capabilities. Organizations are using deep learning networks to get valuable insights from huge amount of data. This is done to provide innovative products and better improved customer experiences, thereby raising revenue opportunities for the market. The global deep learning market is anticipated to reach USD 28.83 Bn and expand at a CAGR of 48.4% during the forecast period of 2018-2023.

Deep learning techniques are used to develop new technologies such as natural language processing and visual data mining, to enhance product offerings. The growing need for deep learning in database systems, fraud detection and cyber security, is driving the growth process of data mining applications in the deep learning market. The market is classified into three primary segments – based on solution, application and end user.
Based on solution: Hardware, software and services
Based on application: Image recognition, signal recognition, data mining, and others
Based on end user: Healthcare, BFSI, aerospace and defense, automotive, retail and media and entertainment and others (manufacturing, oil, gas and energy)
On the basis of regions, the market is segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa.

Key growth factors

Deep learning offers faster and better memory utilization in comparison to traditional computing systems. Rising usage of deep learning technology among various industries such as automotive, advertisement, medical fuel the growth of the market. Robust research and development for the expansion of better processing hardware for deep learning, growing necessity for hardware platforms with high computing power to execute deep learning algorithms are key driving factors of deep learning market. Increasing acceptance of cloud based technology, high usage of deep learning in big data analytics, and rising applicability in healthcare and autonomous vehicles are accelerating growth.

Threats and key players

Deep learning requires high-performance hardware, which is not easily available. Greater complexities in hardware owing to complex algorithm in deep learning technology, can hamper the growth of the market. Many organizations prefer the traditional route over hyper parameter optimization, thereby restricting the revenue growth of the deep learning market.
Some of the prominent competitors in deep learning market are Google Inc., Microsoft Corporation, Qualcomm Technologies, Inc., IBM Corporation, Intel Corporation, General Vision Inc. and NVIDIA Corporation, etc.

What’s covered in the report?

1. Overview of the global deep learning market.
2. Market drivers and challenges of the global deep learning market.
3. Market trends in global deep learning market.
4. Historical, current and forecasted market size data for the segment based on solution.
5. Historical, current and forecasted market size data for the segment based on application.
6. Historical, current and forecasted market size data for the segment based on end user.
7. Historical, current and forecasted regional (North America, Europe, Asia-Pacific, Latin America, the Middle East & Africa) market size data for the deep learning market.
8. Historical, current and forecasted market size data for region-wise segments.
9. Analysis of company profiles of major competitors operating in the market.

Why buy?

1. Understand the demand for deep learning to determine the viability of the market
2. Determine the developed and emerging markets of deep learning
3. Identify the challenge areas and address them
4. Develop strategies based on the drivers, trends and highlights for each of the segments
5. Evaluate the value chain to determine the workflow and to get an idea of the current position where you are placed
6. Recognize the key competitors of this market and respond accordingly
7. Knowledge of the initiatives and growth strategies taken by the major companies and decide the direction of further growth
8. Define the competitive positioning by comparing the products and services with the key players in the market
9. Recognize the extent and nature of the start-ups providing deep learning solutions


Chapter 1: Executive Summary
1.1 Market Scope and Segmentation
1.2 Key Questions Answered in This Study
1.3 Executive Summary I
1.4 Executive Summary II

Chapter 2: Introduction
2.1. Blockchain technology-Functionality
2.2. Blockchain Application
2.3. Blockchain use cases
2.4. Value chain-Blockchain technology market

Chapter 3: Global Blockchain Technology Market overview
3.1. Overview – key observations, historical (2016-2017) and forecasted (2018-2023) market size (USD bn), geography wise market size (USD bn) in 2017
3.2. Market adoption
3.3. Market trends

Chapter 4: Blockchain Technology Market regional market overview
4.1. North America- Historical (2016-2017) and forecasted (2018-2023) market size (USD Bn), drivers, trends and challenges
4.2. Europe– Historical (2016-2017) and forecasted (2018-2023) market size (USD Bn), drivers, trends and challenges
4.3. Asia Pacific– Historical (2016-2017) and forecasted (2018-2023) market size (USD Bn), drivers, trends and challenges
4.4. Latin America– Historical (2016-2017) and forecasted (2018-2023) market size (USD Bn), drivers, trends and challenges
4.5. Middle East & Africa– Historical (2016-2017) and forecasted (2018-2023) market size (USD Bn), drivers, trends and challenges

Chapter 5: Blockchain Technology Market segmentation by industries
5.1. Global industry segmentation by BFS, Insurance, Supply Chain, Healthcare and other industries – Industry overview, market share
5.1.1. North America industry segmentation by BFS, Insurance, Supply Chain, Healthcare and other industries – Revenue contribution (historical and forecasted), drivers, and key competitors
5.1.2. Europe industry segmentation by BFS, Insurance, Supply Chain, Healthcare and other industries – Revenue contribution (historical and forecasted), drivers, and key competitors
5.1.3. Asia Pacific industry segmentation by BFS, Insurance, Supply Chain, Healthcare and other industries – Revenue contribution (historical and forecasted), drivers, and key competitors
5.1.4. Latin America industry segmentation by BFS, Insurance, Supply Chain, Healthcare and other industries – Revenue contribution (historical and forecasted), drivers, and key competitors
5.1.5. Middle East & Africa industry segmentation by BFS, Insurance, Supply Chain, Healthcare and other industries – Revenue contribution (historical and forecasted), drivers, and key competitors

Chapter 6: Blockchain Technology Market segmentation by type – Private, public and mixed
6.1. Market overview by type – revenue contribution, market growth, influential factors, adoption

Chapter 7: Patent Analysis
7.1. Patent Overview
7.2. Patents Filed/ Published (2012 – 2016)
7.3. Patents by Major Companies
7.4. Patents by Geographical Origin
7.5. Patents by Platform
7.6. Patents by Ledger Types
7.7. Patents by Authentication
7.8. Patents by Application types

Chapter 8: Company Profiles
8.1. Microsoft Corporation
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence
8.2. IBM
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence
8.3. Accenture
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence
8.4. Deloitte
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence
8.5. Capgemini
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence
8.6. Cognizant
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence
8.7. Infosys
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence
8.8. Tata Communication Services
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence
8.9. VirtusaPolaris
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence
8.10. Wipro
o Company Snapshot
o Key People
o Financial Standing
o Blockchain Offering
o Focus Area
o Recent Initiatives
o Key Verticals
o Geographical Presence

Chapter 9: Start-up Company Overview
9.1. Chain (*)
o Overview
o Key People
o Investor
o Client/Partners
o Recent Initiatives
(*) similar information is provided for all the below companies
9.2. Consensys
9.3. R3 CEV
9.4. Ripple
9.5. Guardtime
9.6. Gem
9.7. Everledger
9.8. Ascribe

Chapter 10: Conclusion
10.1. Blockchain Opportunity
10.2. Conclusion

Chapter 11: Appendix
11.1. List of Tables
11.2. Research Methodology
11.3. Assumptions
11.4. About Netscribes Inc.

Additional information

Publisher

Geography Covered

Date Published

Pages

Format