Class result prediction using machine learning
S. K. Pushpa, T N Manjunath, T V Mrunal, Amartya Singh, C. Suhas · 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon) · 2017
More than 2.5 quintillion bytes of data is being generated across the globe. In fact, this data is as much as 90% of the data in the world today, and has been created in the last two years alone. Big data describes the large volume of data that inundates a business on a day to day basis. Huge amount of data is being generated by everything around us at all times and is produced by every digital process and social media exchange through systems, sensors, mobile devices, etc. Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. To extract meaningful value from big data, one needs optimal processing power, analytics capabilities and skills. Using the concept of machine learning, a number of algorithms are explored in order to predict the result of class students. Based on the performance of the students in previous semester, and the scores of internal examinations of the current semester, the final result, whether the student passes or fails the current semester is computed before the final examination actually takes place.