Implementation of Imputer: Sequence Modelling via Imputation and Dynamic Programming in PyTorch

An abstract missing value imputation library. EasyImputer employs the right kind of imputation technique based on the statistics of missing data.

This project contains transformers for missing value imputation

Build machine learning model to predict whether a house will sell or not based on a set of features. The results will be presented in the form of interactive widgets in jupyter notebook for technical audience that can be used to make informed decision about selling their properties.

Machine learning models and approaches

Data Imputer API in Python

Data cleaning tools, handling missing data, categorical data, feature scaling

Handling numerical missing data using, interpolation, spline interpolation, simple imputer, etc on weather data

Data Cleaning and Data Visualization with python libraries like numpy , pandas, sklean,seaborn, matplotlib-pyplot

This Flask app predicts house prices using a RandomForestRegressor model trained on a housing dataset. It includes data pre-processing with pipelines and imputers, stratified train-test splitting, and a user input form. Predictions are displayed on the web page, making it ideal for learning basic machine learning deployment with Flask.