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Lakshya

LAKSHYA PRESENTS A ML Model based Predictor for Malaria

The problem Lakshya solves

The proposed system will integrate weather and temperature data to predict the spread of communicable diseases.Weather, Temperature, Seasonal and Environmental-based Prediction.The proposed system will integrate weather and temperature data to predict the spread of communicable diseases.
Factors such as temperature, humidity, and rainfall can significantly impact the spread of communicable diseases by affecting the survival and reproduction of vectors such as mosquitoes or by
affecting the growth of bacteria or viruses. Weather, Temperature, Seasonal and Environmental-based Prediction.The proposed system will integrate weather and temperature data to predict the spread of communicable diseases. Factors such as temperature, humidity, and rainfall can significantly impact the spread of communicable diseases by affecting the survival and reproduction of vectors such as mosquitoes or by affecting the growth of bacteria or viruses. For example, warmer
temperatures can increase the rate of mosquito reproduction and therefore the risk of malaria.

Challenges we ran into

.1. Data set collection was a major task and then training of the model.
2. Data Cleaning.

Technologies used

Discussion