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 candidates more likely to have the visa certified.

Sentiment Analysis of Lockdown in India During COVID-19:A Case Study on Twitter

This repository aims to address the critical issue of identifying and understanding suicide ideation in social media conversations, specifically focusing on Twitter data.

No description provided.

For this project, I used four different classification algorithms to detect fraudulent credit card transactions.

This research advances credit card fraud detection by integrating machine learning and deep learning techniques. Key findings include improved model adaptability through hyperparameter tuning.

🚀 Predicting diabetes risk in females with AdaBoost Classifier! 💻✨

Classification

Predicting transaction fraud using classification problems such as Guardian Boosting as well as user interfaces using Streamlite, Accuracy: 98% AUC-ROC

This project focuses on predicting depression among students using various machine learning models. It explores relationships between key factors like sleep duration, gender, financial stress, work/study hours, and academic pressure with depression. The study leverages EDA and multiple ML algorithms to achieve high prediction accuracy.

I made a model which can detect if a person has Chronic Kidney Disease by inputting some data. I also made a WebApp using Heroku

An algorithmic trading strategy incursion using Adaboost machine learning classifier, to create the first volatility security suitable for long term investors.

Predict the winning probability of white player in a chess game on the basis of first move of white player and first move of black player. In the dataset all the set of moves are given but I choose to predict the white winner the first move

In this project I intend to predict customer churn on bank data.

Decision Tree and Decision Forest for Matlab/Octave and Python

With this model: the amount of backlog would be reduced significantly, the amount of staff needed to do the job would be reduced drastically, the processing time would be shortened significantly and more cases of fraudulent transactions would be tracked down in a given amount of data processed - more than 40% increase in efficiency!

Human Resources Employee Turnover Analysis

This project was conducted to predict recharge delay using regression techniques and customer churn using classification models

Classification Project for SDAIA T5 Data Science Bootcamp. This project will choose the best classification model to predict whether a loan is a short-term loan or a long-term loan, based on some features.

No description provided.

Machine Learning Bot is a Jupyter Notebook based application prototype to perform algorithmic trading using a Machine Learning algorithm.

No description provided.

Machine Learning - Practical assignment

Gain a complete and accurate understanding of the disease you’re dealing with.

This repo is about the cyber security project where malware is detected and classified

No description provided.

Goal Using the data collected from existing customers, build a model that will help the marketing team identify potential customers who are relatively more likely to subscribe term deposit and thus increase their hit ratio

Employ different techniques to train and evaluate models with unbalanced classes. Evaluate the performance of these models and make recommendations on their suitability to predict credit risk.

Machine Learning helps in predicting the Heart diseases, and the predictions made are quite accurate.

In my Bangla news categorization project, I utilized XGBoost for efficient pattern recognition, SVM for handling non-linear relationships, and an ensemble of Random Forest, AdaBoost, and Logistic Regression to collectively enhance precision. This diverse approach ensures robust and accurate classification of Bangla news articles.