Correlating lockdowns, mortality rates and air pollution: a deep learning imbued study of COVID-19

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Xehetasun bibliografikoak
Egile Nagusiak:	Tabassum, Tahia, Rahman, Saiham, Mahmood, Moosfiqur Hassan, Siam, Md. Fahim, Mumu, Sadia Anika
Beste egile batzuk:	Alam, Md. Golam Rabiul
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2021
Gaiak:	COVID-19 LSTM Air Pollution K-Means Clustering COVID-19 Mortality Regression COVID-19 Lockdowns COVID-19 (Disease)
Sarrera elektronikoa:	http://hdl.handle.net/10361/15400

Deskribapena
Gaia:	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Antzeko izenburuak