An information retrieval system which consists of various techniques' implementations like indexing, tokenization, stopping, stemming, page ranking, snippet generation and evaluation of results

Apply supervised machine learning techniques and an analytical mind on data collected for the U.S. census to help CharityML (a fictitious charity organization) identify people most likely to donate to their cause

Classification Metric Manager is metrics calculator for machine learning classification quality such as Precision, Recall, F-score, etc.

Submissions for Data Science: Principles, Algorithms, and Applications (CS839) @ UW-Madison

Identifying Books on Library Shelves using Supervised Deep Learning.

A Swift implementation of mAP computation for Yolo-style detections

Amex Analyze This is a data science competition held by American Express across all the Indian Institute of Technology Institutes across India. I had participated in this competition in 2018, it was based on predictive modelling where we need to train a model to solve a bank problem - Analyze This 2018

Fraud detection with SMOTE (Synthetic Minority Over-sampling Technique)

LSTM based model for Named Entity Recognition Task using pytorch and GloVe embeddings

Report various statistics stemming from a confusion matrix in a tidy fashion. 🎯

Resample precision-recall curves correctly!

📊Course 3: Machine Learning Specialization course of Coursera by the University of Washington on Classification

Unofficial Python implementation of "Precision and Recall for Time Series".

Developed a Convolutional Neural Network based on VGG16 architecture to diagnose COVID-19 and classify chest X-rays of patients suffering from COVID-19, Ground Glass Opacity and Viral Pneumonia. This repository contains the link to the dataset, python code for visualizing the obtained data and developing the model using Keras API.

Using 21 predictor variables and applying simple Logistic Regression, predicting whether a particular customer will switch to another telecom provider or not. In telecom terminology, this is referred to as churning and not churning, respectively.

Time-series Aware Precision and Recall for Evaluating Anomaly Detection Methods

The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidate…

The aim is to develop an ML- based predictive classification model (logistic regression & decision trees) to predict which hotel booking is likely to be canceled. This is done by analysing different attributes of customer's booking details. Being able to predict accurately in advance if a booking is likely to be canceled will help formulate prof…