5_Telecom.pptx - TELECOM INDUSTRY TECHNOLOGY MACHINE LEARNING BYDIKSHA BANSAL(15KA PRAKHAR MAHESHWARI(34KA DHARSHAN K(74KB DURGESH PANDEY(75KB MADHURIMA

5_Telecom.pptx - TELECOM INDUSTRY TECHNOLOGY MACHINE...

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TECHNOLOGY- MACHINE LEARNING TELECOM INDUSTRY BY - DIKSHA BANSAL(15KA) PRAKHAR MAHESHWARI(34KA) DHARSHAN K(74KB) DURGESH PANDEY(75KB) MADHURIMA AGRAWAL(86KB) PIYUSH VIJAYAN(152KC) UDAY MOHAN SINGH(169KC)
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Machine learning would refer to the system, a technological system capable of acquiring and integrating knowledge automatically. This also includes the ability and capability to learn from experience, training and analytical observation which then results in a system that persistently improves and functions efficiently. Training is an important step in Machine learning and for training any machine learning algorithm for instance a neu- ral network , There are 4 entities that are required which are Data Model Objective Function Optimization Algorithm Supervised Learning Here the label is known, Based on which the value or class is modelled or pre- dicted Unsupervised Learning This is more concerned with pattern recognition where the label is not known, hence a pattern is predicted Semi-super- vised learning. This type of leaning is a combination of both super- vised and unsupervised learning Ma- chine Learn- ing al- gorithm s Super- vised two class & Multi class classifica- tion Unsuper- vised Anomaly detection Super- vised re- gression Simple and multiple linear regression Support Vec- tor machine K-means clustering Artificial Neu- ral networks OVERVIEW
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CHALLENGES 01 Telecoms everywhere are attracting more users if the amount of data they’re capturing about their customers and networks continue to grow without a proper plan around how to store, manage, and utilize that data, then every new project is at risk of falling apart. Data is soloed, queries take hours or days to complete, and nobody in the company has a complete view into what’s actually happening in the business.
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