Projects
Here are the few key projects on which I worked upon during my learning journey
Patient survival in hospital
Using the dataset of Greenland's hospital patients I have analysed the features using feature selection methods RFE, Boruta and achieved the best results using xgboost to predict whether a patient will survive or not.
This analysis will help hospital to analyse the main factor for the death of majority of the patients.
Twitter sentiments analysis
After doing data pre-processing and
exploratory data analysis I have used
the bag of words and word embedding
model to train a model and achieved
best results with hyperparameter tuning
using xgboost algorithm.
Predicting employee attrition
Using IBM employee dataset , after standardising and normalising the data into same format using label and one-hot encoding Random forest classifier algorithm gave the best results on test data and gave the probability for chances of a employer to be kick out of the organisation.
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