Deep Learning Software Market 2025 with Focus on Emerging Technologies, Global Trends, Competitive Landscape, Regional Analysis & Forecasts

Deep Learning is a subfield of machine learning. It is concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Deep learning models are loosely related to information processing and communication patterns in a biological nervous system, for instance neural coding which attempts to define a relationship between various stimuli and associated neuronal responses in the brain.

According to a new report published by Reports Monitor titled, “Deep Learning Software Market By Applications and End-User: Global Opportunity Analysis and Industry Forecast, 2017–2025,” the Deep Learning Software Market was valued at XX million in 2016, and is projected to reach at XX million by 2025, growing at a CAGR of XX% from 2017 to 2025. North America dominates the Deep Learning Software Market, both in terms of volume and value, and is expected to maintain this trend throughout the forecast period. 

Deep Learning is a subfield of machine learning. It is concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Deep learning models are loosely related to information processing and communication patterns in a biological nervous system, for instance neural coding which attempts to define a relationship between various stimuli and associated neuronal responses in the brain. Deep learning can be supervised, semi-supervised or unsupervised.

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Deep learning architectures foe instance deep neural networks, deep belief networks and recurrent neural networks have been applied to fields which includes computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics and drug design. In short, Deep learning software mimics brain activity, and has ability to learn and recognize patterns, audio or even visuals stored in memory.

Increased usage of deep learning in Big Data analytics, increased adoption of cloud technology, need of computing power are some of the growth factors for Deep-Learning-Software market. Deep learning program helps in cutting down the cost of labor & machines and additionally it improves the system efficiency.

Global Deep-Learning-Software market has been segmented majorly on the basis of Applications (Data Mining, Image Recognition, Signal Recognition, and others) & End-User (Banking, Financial Services and Insurance (BFSI), aerospace & defense, Healthcare and life sciences, Manufacturing Retail, Telecommunication and media and others).

North America is expected to be the largest market for Deep-Learning-Software. Heavy investments in research & developments, existence of large end-user industries and changing business dynamics, and emergence of startups are some of the factors that are fuelling the growth of deep learning market in this region.

Key Question Answered:
• What will be the market size in 2025 and at what rate it will grow?
• What trends, barriers, challenges are influencing its growth?
• Who are the major key players in Global Deep Learning Software Market and what are their strategies?
• Which vertical industry is expected to show major growth?
• What segment and region will lead the market and why?

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The major companies profiled in the report include: AWS, General Vision, Google, Graphcore, IBM, Intel, Microsoft, NVIDIA, Qualcomm, Sensory Inc., and Xilinx.

The study for Global Deep Learning Software Market will provide market size, estimates and forecast based on the following years: 

Historic data: 2015  Base Year Estimate: 2016  Forecast: 2017 to 2025  

The report has been categorized in two distinctive sections, where the first category titled as Market Overview provides a holistic view of the market, key trends, drivers, challenges/restraints or opportunities with their current and expected impact on the overall industry sales.

Our analyst implement several qualitative tools such as Ansoff’s Matrix, PESTEL analysis, Porter’s five force analysis among other to interpret and represent key industry findings.

The second section of the study provides market size, estimates and forecast for key market segments and regional market. The final part of the report highlights key manufacturers/vendors operating in the associated market. 

1. Introduction

1.1. Market Definition

1.2. Market Scope 

2. Research Methodology

2.1. Primary Research

2.2. Secondary Sources

2.3. Assumptions & Exclusions 

3. Market Overview

3.1. Research Report Segmentation & Scope

3.2. Key Market Trend Analysis

3.2.1. Market Drivers

3.2.2. Market Restraint/Challenges

3.2.3. Market Opportunities

3.3. Porter’s Five Forces Analysis

3.4. Potential Venture Avenues

3.5. Market Share Analysis, 2016 

4. Applications Overview

4.1. Introduction

4.2. Market Size & Forecast, 2015 to 2025

4.2.1. Data Mining

4.2.2. Image Recognition

4.2.3. Signal Recognition

4.2.4. Others

(Note: The segments mentioned above are tentative in nature and are subject to change as the research progresses) 

5. End User Overview

5.1. Introduction

5.2. Market Size & Forecast, 2015 to 2025

5.2.1. Banking, Financial Services and Insurance (BFSI)

5.2.2. Government and Defence

5.2.3. Healthcare and life sciences

5.2.4. Manufacturing

5.2.5. Retail

5.2.6. Telecommunication and media

5.2.7. Others

(Note: The segments mentioned above are tentative in nature and are subject to change as the research progresses) 

6. Regional Overview

6.1. Introduction

6.2. Market Size & Forecast, 2015 to 2025

6.2.1. North America

6.2.1.1. U.S.

6.2.1.2. Canada

6.2.1.3. Mexico

6.2.2. Europe

6.2.2.1. UK

6.2.2.2. Germany

6.2.2.3. France

6.2.2.4. Italy

6.2.2.5. Spain

6.2.2.6. Rest of Europe

6.2.3. Asia-Pacific

6.2.3.1. China

6.2.3.2. India

6.2.3.3. Japan

6.2.3.4. South Korea

6.2.3.5. Rest of Asia-Pacific

6.2.4. LAMEA

6.2.4.1. Brazil

6.2.4.2. UAE

6.2.4.3. South Africa

6.2.4.4. Rest of LAMEA

(Note: The segments mentioned above are tentative in nature and are subject to change as the research progresses) 

7. Manufacturer/ Vendor Profile

7.1. The following attributes will be considered while profiling key manufacturers in this industry:

7.1.1. Company Overview

7.1.2. Financial Synopsis

7.1.3. Recent Developments

7.1.4. R&D Investments (if any)

7.1.5. Strategy Overview (Analyst Perspective)

7.1.6. Product Portfolio

7.2. Companies Profiled

7.2.1. AWS

7.2.2. General Vision

7.2.3. Google

7.2.4. Graphcore

7.2.5. IBM

7.2.6. Intel

7.2.7. Microsoft

7.2.8. NVIDIA

7.2.9. Qualcomm

7.2.10. Sensory Inc.

7.2.11. Xilinx

(Note: The companies mentioned above are tentative in nature, and profiles of other market players not listed here can be included on request.)

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