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.
Dr. Nonita Sharma works in the domain of Time series forecasting, Data Analytics, Wireless Sensor Networks.Dr. Deepti Kakkar's area of interest includes Spectrum Sensing in Multihop Networks for Cognitive Radios. Nashreen Sultana works in the area of time series forecasting modelling.
Number of Pages:
LAP LAMBERT Academic Publishing
ARIMA, Forecasting, Time Series, Communicable Diseases, prediction
COMPUTERS / Information Technology