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.

Market Analysis and Insights: Global Machine Learning in Communication Market
In 2021, the global Machine Learning in Communication market size will be US$ million and it is expected to reach US$ million by the end of 2027, with a CAGR of % during 2021-2027.
With industry-standard accuracy in analysis and high data integrity, the report makes a brilliant attempt to unveil key opportunities available in the global Machine Learning in Communication market to help players in achieving a strong market position. Buyers of the report can access verified and reliable market forecasts, including those for the overall size of the global Machine Learning in Communication market in terms of revenue.
On the whole, the report proves to be an effective tool that players can use to gain a competitive edge over their competitors and ensure lasting success in the global Machine Learning in Communication market. All of the findings, data, and information provided in the report are validated and revalidated with the help of trustworthy sources. The analysts who have authored the report took a unique and industry-best research and analysis approach for an in-depth study of the global Machine Learning in Communication market.

Global Machine Learning in Communication Scope and Market Size
Machine Learning in Communication market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Machine Learning in Communication market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application in terms of revenue and forecast for the period 2016-2027.

Segment by Type
Cloud-Based
On-Premise

Segment by Application
Network Optimization
Predictive Maintenance
Virtual Assistants
Robotic Process Automation (RPA)

By Region
North America
U.S.
Canada
Europe
Germany
France
U.K.
Italy
Russia
Nordic
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

By Company
Amazon
IBM
Microsoft
Google
Nextiva
Nexmo
Twilio
Dialpad
Cisco
RingCentral