The Machine learning still needs data scientists to optimise results
"Machine learning is not a one-size-fits-all technology, but a growing library of technologies that need to be understood and deployed correctly to achieve meaningful results."
Machine learning (ML) can help communications service providers (CSPs) to manage the growing expense of creating and maintaining algorithms built by data scientists. The ability to allow machines to learn insights and relationships through the application of ML techniques means analytics can be applied to more use cases. In addition, ML is a key component in the creation of artificial intelligence, which enables applications to learn from their environments. However, ML is not simple and CSPs and vendors need to carefully select which ML algorithms are used for each use case.
This country report and accompanying data annex provide a comprehensive overview of Hungary's telecoms market, including KPIs and data on subscribers, penetration, revenue and ARPU. The report analyses the strategiesView Report
Global automotive Aftermarket sector will lead to large volume of connected devices and significant revenue as such, competition for contracts.View Report
Global Artificial Intelligence in Construction Market Size study, by Application (Project Management, Field Management, Risk Management, Schedule Management, Supply-Chain Management, Others), by Industry (Residential, Institutional Commercial, Heavy construction, Others), by Component (Solutions, Services), by Stage of Construction (Pre-Construction, Construction Stage, Post-Construction), by Technology (Machine Learning & Deep Learning, Natural Language Processing), by Deployment (Cloud, On-Premises) and Regional Forecasts 2018-2025
Global Artificial Intelligence in Construction Market to reach USD XX billion by 2025.Global Artificial Intelligence in Construction Market valued approximately USD XX billion in 2017 is anticipated to grow withView Report
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