Ensemble Modelling for Disease Forecasting - Sharma, Nonita; Kakkar, Deepti; Sultana, Nashreen
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  • Broschiertes Buch

The world is filled with lots and lots of data. Be it data in the form of pictures, statistical values, videos, music, words, etc. Traditionally human being is able to recognize and extract a meaningful pattern out of such data. But as the volume of data increases, it becomes impossible for a human being to extract it meaningfully. To get a meaning out of such bulk data, a set of tools are required with the help of which a machine can be taught to recognize the pattern and extract the information. The term machine learning came into existence. Time is an importantfactor when it comes to data…mehr

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Produktbeschreibung
The world is filled with lots and lots of data. Be it data in the form of pictures, statistical values, videos, music, words, etc. Traditionally human being is able to recognize and extract a meaningful pattern out of such data. But as the volume of data increases, it becomes impossible for a human being to extract it meaningfully. To get a meaning out of such bulk data, a set of tools are required with the help of which a machine can be taught to recognize the pattern and extract the information. The term machine learning came into existence. Time is an importantfactor when it comes to data where the sudden change in the values at a particular time can have a huge impact on the outcome. Smart forecasting tools powered by data science is necessary to successfully deal with capacity and strategic planning which is required to handle the scenario and save lives. The purpose of this book is to present an efficient model that can forecast the values more accurately in a particular field.
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Autorenporträt
Nonita Sharma is currently working as an Assistant Professor in the Department of Computer Science & Engineering, Dr. B. R. Ambedkar National Institute of Technology Jalandhar. Her research interests include Wireless Sensor Networks, IoT, Big Data Analytics, and Data Mining.