Credit Card Transaction Fraud is a very common problem for banks and they use machine learning models to tackle this problem.
Imputed missing data,created custom features,normalize and encode features Performed exploratory data analysis of features Handled imbalanced data using SMOTE and custom loss function.
Preprocessed/encoded documents into vector for entire corpus Implemented local sensitive hashing(LSH) for multiple universe (different set of random planes) Developed document search using approximate k-nearest neighbor and LSH
Parts of speech tagging the process of assigning a part-of-speech tag (Noun, Verb, Adjective…) to each word in an input text. I have trained two different model HMM which is generative model and MEMM which is discriminative.
Due to the second wave of covid-19, There is an unprecedented surge of covid-19 in india and we wanted to analyze the sentiment of public on the basis of tweeter. We have used stanford core NLP to analyze the tweets.