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 report offers detailed coverage of Machine Learning in Communication industry and main market trends. The market research includes historical and forecast market data, demand, application details, price trends, and company shares of the leading Machine Learning in Communication by geography. The report splits the market size, by volume and value, on the basis of application type and geography.
The report forecast global Machine Learning in Communication market to grow to reach xxx Million USD in 2020 with a CAGR of xx% during the period 2021-2025.
First, this report covers the present status and the future prospects of the global Machine Learning in Communication market for 2015-2025.
And in this report, we analyze global market from 5 geographies: Asia-Pacific[China, Southeast Asia, India, Japan, Korea, Western Asia], Europe[Germany, UK, France, Italy, Russia, Spain, Netherlands, Turkey, Switzerland], North America[United States, Canada, Mexico], Middle East & Africa[GCC, North Africa, South Africa], South America[Brazil, Argentina, Columbia, Chile, Peru].
Key Companies
Amazon
IBM
Microsoft
Google
Nextiva
Nexmo
Twilio
Dialpad
Cisco
RingCentral
At the same time, we classify Machine Learning in Communication according to the type, application by geography. More importantly, the report includes major countries market based on the type and application.
Market Segment as follows:
Market by Order Type
Cloud-Based
On-Premise
Market by Application
Network Optimization
Predictive Maintenance
Virtual Assistants
Robotic Process Automation (RPA)
By Region
Asia-Pacific[China, Southeast Asia, India, Japan, Korea, Western Asia]
Europe[Germany, UK, France, Italy, Russia, Spain, Netherlands, Turkey, Switzerland]
North America[United States, Canada, Mexico]
Middle East & Africa[GCC, North Africa, South Africa]
South America[Brazil, Argentina, Columbia, Chile, Peru]
The research provides answers to the following key questions:
• What is the estimated growth rate and market share and size of the Machine Learning in Communication market for the forecast period 2021 - 2025?
• What are the driving forces in the Machine Learning in Communication market for the forecast period 2021 - 2025?
• Who are the prominent market players and how have they gained a competitive edge over other competitors?
• What are the market trends influencing the progress of the Machine Learning in Communication industry worldwide?
• What are the major challenges and threats restricting the progress of the industry?
• What opportunities does the market hold for the prominent market players?