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Global Machine Learning in Communication Market Research Report 2024

Global Machine Learning in Communication Market Research Report 2024

Publishing Date : Feb, 2024

License Type :
 

Report Code : 1899390

No of Pages : 86

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Synopsis
The field of communications is traditionally built on precise mathematical models that are well understood and have been shown to work exceptionally well for many practical applications. Unfortunately, communication systems designers have been forced to push the boundaries to such an extent that in many applications conventional mathematical models and signal processing techniques are no longer sufficient to accurately describe the encountered complex scenarios. Specifically, there is an increasing number of cases where rigorous mathematical models are either not known or are entirely impractical from a computational perspective. Machine learning methods can come to the rescue as they do not require rigid pre-defined models and can extract meaningful structure from large amounts of data to provide useful results.
The global Machine Learning in Communication market was valued at US$ million in 2023 and is anticipated to reach US$ million by 2030, witnessing a CAGR of % during the forecast period 2024-2030.
The Global Mobile Economy Development Report 2023 released by GSMA Intelligence pointed out that by the end of 2022, the number of global mobile users would exceed 5.4 billion. The mobile ecosystem supports 16 million jobs directly and 12 million jobs indirectly.
According to our Communications Research Centre, in 2022, the global communication equipment was valued at US$ 100 billion. The U.S. and China are powerhouses in the manufacture of communications equipment. According to data from the Ministry of Industry and Information Technology of China, the cumulative revenue of telecommunications services in 2022 was ¥1.58 trillion, an increase of 8% over the previous year. The total amount of telecommunications business calculated at the price of the previous year reached ¥1.75 trillion, a year-on-year increase of 21.3%. In the same year, the fixed Internet broadband access business revenue was ¥240.2 billion, an increase of 7.1% over the previous year, and its proportion in the telecommunications business revenue decreased from 15.3% in the previous year to 15.2%, driving the telecommunications business revenue to increase by 1.1 percentage points.
This report aims to provide a comprehensive presentation of the global market for Machine Learning in Communication, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Machine Learning in Communication.
Report Scope
The Machine Learning in Communication market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Machine Learning in Communication market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Machine Learning in Communication companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
Amazon
IBM
Microsoft
Google
Nextiva
Nexmo
Twilio
Dialpad
Cisco
RingCentral
Segment by Type
Cloud-Based
On-Premise
Segment by Application
Network Optimization
Predictive Maintenance
Virtual Assistants
Robotic Process Automation (RPA)
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Machine Learning in Communication companies’ competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
Index
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Machine Learning in Communication Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 Cloud-Based
1.2.3 On-Premise
1.3 Market by Application
1.3.1 Global Machine Learning in Communication Market Growth by Application: 2019 VS 2023 VS 2030
1.3.2 Network Optimization
1.3.3 Predictive Maintenance
1.3.4 Virtual Assistants
1.3.5 Robotic Process Automation (RPA)
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Machine Learning in Communication Market Perspective (2019-2030)
2.2 Machine Learning in Communication Growth Trends by Region
2.2.1 Global Machine Learning in Communication Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Machine Learning in Communication Historic Market Size by Region (2019-2024)
2.2.3 Machine Learning in Communication Forecasted Market Size by Region (2025-2030)
2.3 Machine Learning in Communication Market Dynamics
2.3.1 Machine Learning in Communication Industry Trends
2.3.2 Machine Learning in Communication Market Drivers
2.3.3 Machine Learning in Communication Market Challenges
2.3.4 Machine Learning in Communication Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Machine Learning in Communication Players by Revenue
3.1.1 Global Top Machine Learning in Communication Players by Revenue (2019-2024)
3.1.2 Global Machine Learning in Communication Revenue Market Share by Players (2019-2024)
3.2 Global Machine Learning in Communication Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Machine Learning in Communication Revenue
3.4 Global Machine Learning in Communication Market Concentration Ratio
3.4.1 Global Machine Learning in Communication Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Machine Learning in Communication Revenue in 2023
3.5 Machine Learning in Communication Key Players Head office and Area Served
3.6 Key Players Machine Learning in Communication Product Solution and Service
3.7 Date of Enter into Machine Learning in Communication Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Machine Learning in Communication Breakdown Data by Type
4.1 Global Machine Learning in Communication Historic Market Size by Type (2019-2024)
4.2 Global Machine Learning in Communication Forecasted Market Size by Type (2025-2030)
5 Machine Learning in Communication Breakdown Data by Application
5.1 Global Machine Learning in Communication Historic Market Size by Application (2019-2024)
5.2 Global Machine Learning in Communication Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Machine Learning in Communication Market Size (2019-2030)
6.2 North America Machine Learning in Communication Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America Machine Learning in Communication Market Size by Country (2019-2024)
6.4 North America Machine Learning in Communication Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Machine Learning in Communication Market Size (2019-2030)
7.2 Europe Machine Learning in Communication Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe Machine Learning in Communication Market Size by Country (2019-2024)
7.4 Europe Machine Learning in Communication Market Size by Country (2025-2030)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Machine Learning in Communication Market Size (2019-2030)
8.2 Asia-Pacific Machine Learning in Communication Market Growth Rate by Region: 2019 VS 2023 VS 2030
8.3 Asia-Pacific Machine Learning in Communication Market Size by Region (2019-2024)
8.4 Asia-Pacific Machine Learning in Communication Market Size by Region (2025-2030)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Machine Learning in Communication Market Size (2019-2030)
9.2 Latin America Machine Learning in Communication Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America Machine Learning in Communication Market Size by Country (2019-2024)
9.4 Latin America Machine Learning in Communication Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Machine Learning in Communication Market Size (2019-2030)
10.2 Middle East & Africa Machine Learning in Communication Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa Machine Learning in Communication Market Size by Country (2019-2024)
10.4 Middle East & Africa Machine Learning in Communication Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Amazon
11.1.1 Amazon Company Detail
11.1.2 Amazon Business Overview
11.1.3 Amazon Machine Learning in Communication Introduction
11.1.4 Amazon Revenue in Machine Learning in Communication Business (2019-2024)
11.1.5 Amazon Recent Development
11.2 IBM
11.2.1 IBM Company Detail
11.2.2 IBM Business Overview
11.2.3 IBM Machine Learning in Communication Introduction
11.2.4 IBM Revenue in Machine Learning in Communication Business (2019-2024)
11.2.5 IBM Recent Development
11.3 Microsoft
11.3.1 Microsoft Company Detail
11.3.2 Microsoft Business Overview
11.3.3 Microsoft Machine Learning in Communication Introduction
11.3.4 Microsoft Revenue in Machine Learning in Communication Business (2019-2024)
11.3.5 Microsoft Recent Development
11.4 Google
11.4.1 Google Company Detail
11.4.2 Google Business Overview
11.4.3 Google Machine Learning in Communication Introduction
11.4.4 Google Revenue in Machine Learning in Communication Business (2019-2024)
11.4.5 Google Recent Development
11.5 Nextiva
11.5.1 Nextiva Company Detail
11.5.2 Nextiva Business Overview
11.5.3 Nextiva Machine Learning in Communication Introduction
11.5.4 Nextiva Revenue in Machine Learning in Communication Business (2019-2024)
11.5.5 Nextiva Recent Development
11.6 Nexmo
11.6.1 Nexmo Company Detail
11.6.2 Nexmo Business Overview
11.6.3 Nexmo Machine Learning in Communication Introduction
11.6.4 Nexmo Revenue in Machine Learning in Communication Business (2019-2024)
11.6.5 Nexmo Recent Development
11.7 Twilio
11.7.1 Twilio Company Detail
11.7.2 Twilio Business Overview
11.7.3 Twilio Machine Learning in Communication Introduction
11.7.4 Twilio Revenue in Machine Learning in Communication Business (2019-2024)
11.7.5 Twilio Recent Development
11.8 Dialpad
11.8.1 Dialpad Company Detail
11.8.2 Dialpad Business Overview
11.8.3 Dialpad Machine Learning in Communication Introduction
11.8.4 Dialpad Revenue in Machine Learning in Communication Business (2019-2024)
11.8.5 Dialpad Recent Development
11.9 Cisco
11.9.1 Cisco Company Detail
11.9.2 Cisco Business Overview
11.9.3 Cisco Machine Learning in Communication Introduction
11.9.4 Cisco Revenue in Machine Learning in Communication Business (2019-2024)
11.9.5 Cisco Recent Development
11.10 RingCentral
11.10.1 RingCentral Company Detail
11.10.2 RingCentral Business Overview
11.10.3 RingCentral Machine Learning in Communication Introduction
11.10.4 RingCentral Revenue in Machine Learning in Communication Business (2019-2024)
11.10.5 RingCentral Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details

Published By : QY Research

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