Fastag Fraud Detection Classification System
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Updated
Jun 24, 2024 - Jupyter Notebook
Fastag Fraud Detection Classification System
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.
Pipeline creation using Pipeline and make_pipeline along with ColumnTransformer and an Estimator
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.
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.
Function Transformer is part of feature engineering it converts probability density function to normal distribution
pipelines chains together multiple steps so that the output of each step is used as input to the next step
Projects: Chatbot, House price prediction with pipeline
This is a simple classification project that predicts whether a wine is of good quality or not.
Kaggle Competition under programme "30 day of ML" by Alexis Cook
How to apply scikit learn pipeline and ColumnTransformer in your Machine learning Project
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