Toolkit for Apache Spark ML for Feature clean-up, feature Importance calculation suite, Information Gain selection, Distributed SMOTE, Model selection and training, Hyper parameter optimization and selection, Model interprability.

Source for book "Feature Engineering A-Z"

Anomaly detection and failure prognosis applied to industrial machines

Numpy and Pandas are one of the most important building blocks of knowledge to get started in the field of Data Science, Analytics, Machine Learning, Business Intelligence, and Business Analytics. This Tutorial Focuses to help the Beginners to learn the core Concepts of Numpy and Pandas and get started with Machine Learning and Data Science.

The code for the survey paper of feature extraction

This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike sharing demand using the Kaggle Bike Sharing demand dataset.

Generalized functional derivative and integral calculus methods for noisy data

Project: What factors impact the accuracy of airfare prediction?

We will analyze a dataset provided by an e-commerce marketplace called [Olist](https://www.olist.com) to answer the CEO's question: Should Olist remove underperforming sellers from its marketplace? How to increase customer satisfaction (so as to increase profit margin) while maintaining a healthy order volume?

It is a Flask-based web application that predicts the likelihood of COVID-19 infection based on user symptoms. The app utilizes a K-Nearest Neighbors (KNN) model trained on relevant medical features to assess COVID-19 risk.

This project focuses on credit risk analysis using SQL, Python, and Power BI. We built an end-to-end pipeline that starts with raw loan applicant data and ends with an interactive dashboard for stakeholders to monitor loan defaults.

A novel feature selection algorithm using ACO-Ant Colony Optimization, to extract feature words from a given web page and then to generate an optimal feature set based on ACO Metaheuristics and normalized weight defined as a learning function of their learned weights, position and frequency of feature in the web page. JAVA based ACO Framework

The "Movie Genre Prediction" project is a comprehensive machine learning system designed to forecast a movie's genre by analyzing its attributes. By employing advanced machine learning methods, it strives to improve genre classification accuracy, offering valuable insights to creators, film aficionados, and the entertainment sector.

Explore an ML model with Logistic Regression, SVM, Gradient Boosting, Random Forest, and Decision Tree, enhanced via Hyperparameter Tuning. Experience our GUI-based ML model with 82.49% accuracy. Try it now!

Machine Learning project to predict popularity of NYT articles

Ipny and HTML files EDA Case Studies

we aim to predict trends in the Canadian market basket using sentiment analysis techniques. Sentiment analysis involves analyzing text data to determine the sentiment expressed, whether positive, negative, or neutral.

This repository contains the code components of work carried out for analyzing the Medical Provider Fraud Detection dataset with the intent to find most important features to crack down the potentially fraud providers.

Machine Learning Archive