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JMI Team showcases “Monkeypox Detection and Data Analysis” project at IBM Function

New Delhi,MSc Banking and Financial Analytics students of Department of Economics , Jamia Millia Islamia (JMI), New Delhi  who won the first position  in the prestigious Pan India IBM Skills Build Data Analytics Innovation Camp Competition showcased their project “Monkeypox Detection and Data Analysis” in an impressive function organised by IBM at India International Centre  on 30.8.2022. The function was attended by Government officials and IBM executives, winning projects members and a few academia.

As part of the University Placement Cell’s MOU with IBM Skill Build, IBM organized a Data Analytics Innovation camp in which a total of 400+ teams and 3000+ students from all over India participated. JMI team secured the 1st position in the Pan India competition as only four teams qualified for the Final Round (Pitch Night).

Professor Najma Akthar, Hon’ble Vice Chancellor, JMI congratulated the winning team and complemented the Department of Economics and University placement cell for coming out with innovative projects which  are of contemporary and societal relevance. Professor Akthar further added that University will extend all sorts of support to Jamia students for developing such projects and participating in the event competitions.

The team was mentored by HoD, Department of Economics, Prof. Ashere Illiyan and Honorary Deputy Director-UPC, Prof. Moonis Shakeel.

The winning project i.e Monkeypox Detection and Data Analysis aimed to visualize and predict the recent outbreak of Monkeypox. The advent of Monkeypox in 2022, reported by many nations, demonstrated another challenge worldwide as the world was affected due to the onset of COVID 19 in 2020. The project included an analysis of the most affected countries across the world. Machine learning techniques were employed to predict the outbreak of the disease which identified infected persons with up to 95% accuracy. In this project, python libraries like NumPy, pandas, matplotlib, Seaborn, statsmodels, sklearn, and plotly were used. Furthermore, libraries like tensorflow to detect Monkeypox.