A comprehensive analysis and predictive modeling of the "Salary Data.csv" dataset to forecast salaries. Utilizes advanced machine learning techniques, including pipelines and transformers, for robust and accurate predictions.

Machine Learning Drug Classification

T20 World Cup Prediction System -- This GitHub repository contains the code for a T20 World Cup prediction system implemented in Python. The project utilizes popular libraries such as pandas, NumPy, and XGBoost for data manipulation, cleaning, and building predictive models.

Projects: Chatbot, House price prediction with pipeline

This project demonstrates binning and binarization on the Titanic dataset, comparing results with and without numeric encoding. Visualizations highlight the transformations and their impact on survival analysis.

Kaggle Competition under programme "30 day of ML" by Alexis Cook

This dataset contains various demographic and financial features that could be used to build a classification model for predicting loan approval or denial. The loan_status column serves as the target variable for the classification task.

pipelines chains together multiple steps so that the output of each step is used as input to the next step

How to apply scikit learn pipeline and ColumnTransformer in your Machine learning Project

This is a simple classification project that predicts whether a wine is of good quality or not.

https://www.kaggle.com/c/titanic/data

Function Transformer is part of feature engineering it converts probability density function to normal distribution

Pipeline creation using Pipeline and make_pipeline along with ColumnTransformer and an Estimator

Fastag Fraud Detection Classification System

This project combines a Random Forest model with a Streamlit web app to predict car prices based on various factors such as make, model, year, mileage, and more. The overall goal is to create an intuitive, interactive tool that helps users estimate car prices with high accuracy.