Column-Transformer is the method where you can use this feature and you can implement one-hot encoding and OrdinalEncoding both together
-
Updated
Apr 22, 2022 - Jupyter Notebook
Column-Transformer is the method where you can use this feature and you can implement one-hot encoding and OrdinalEncoding both together
House prices dataset exploration and prediction. Workflow includes useful examples of Tensorflow pipelines including k-Nearest Neighbors imputer, Decision Tree Regression and XGBoost Regression
This application predicts the likelihood of obesity and diabetes in a person based on various inputs. It utilizes machine learning models, pipelines, and column transformers to efficiently handle data and provide predictions.
Alzheimer's Disease Classification using Decision tree
Predicting sales volume at various stores
Build ColumnTransformers (Scikit or DaskML) for feature transformation by specifying configs.
Прогнозирование рыночной стоимости автомобилей
Machine Learning course of Piero Savastano 5: ColumnTransformer, SimpleImputer, numpy
This project uses the famous housing price prediction dataset and employs the two supervised ml algorithms (classification and regression).
Car Price Prediction
Applying Advanced Machine Learning techinques such as pipelines and text mining, as well as advanced data engeneering methods like column transformers and estimators.
Data Manipulation of Biopic Dataset
The IPL Win Probability Predictor is a web application built using Streamlit. It uses a machine learning model to predict the probability of a team winning an IPL match based on various factors such as batting team, bowling team, host city, target, score, overs completed, and wickets.
Add a description, image, and links to the column-transformer topic page so that developers can more easily learn about it.
To associate your repository with the column-transformer topic, visit your repo's landing page and select "manage topics."