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Jun 1, 2024 - Jupyter Notebook
categorical-encoding
Here are 19 public repositories matching this topic...
🎬This KickStarter project is about some🎞 foreign films🎥 and music videos🎶. This is an analysis 📽of their 'goal currency' and release time.🎦
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Aug 30, 2020 - Jupyter Notebook
Intermediate Machine Learning Course By Kaggle
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Jul 18, 2024 - Jupyter Notebook
Stacked Classifier
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Jul 17, 2023 - Jupyter Notebook
This repo contains code for experimenting with categorical encoding - WoE, Catboost, Target encoder, and many more.
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Nov 4, 2020
Machine Learning Models
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Jan 23, 2024 - Jupyter Notebook
Encode Categorical Features based on Target/Class
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May 30, 2021 - Python
The project uses Artificial Neural Network and Convolutional Neural Network to classify images into 10 different categories.
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May 20, 2022 - Jupyter Notebook
Exploratory data analysis and model preparation for DrivenData contest: PumpItUp!
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May 23, 2023 - Jupyter Notebook
Successfully established a machine learning model that can accurately classify an e-commerce product into one of four categories, namely "Books", "Clothing & Accessories", "Household" and "Electronics", based on the product's description.
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Sep 22, 2023 - Jupyter Notebook
Customer Churn Analysis
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Jun 15, 2022 - Jupyter Notebook
Heart Risk Level Predicting Regression Model & Web using Feature Engineering and Data Preprocessing 🐤
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May 20, 2023 - Jupyter Notebook
Perform semi automated exploratory data analysis, feature engineering and feature selection on provided dataset by visualizing every possibilities on each step and assisting the user to make a meaningful decision to achieve a low-bias and low-variance model.
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Feb 3, 2023 - Jupyter Notebook
Text Processing RNN leverages RNN and LSTM models for advanced text processing. It features deep learning techniques for NLP tasks, utilizing GloVe for word embeddings, aimed at both educational and practical applications.
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Mar 13, 2024 - Jupyter Notebook
The feature engineering techniques discussed are - dimensionality reduction(pca), scaling(standard scaler, normalizer, minmaxscaler), categorical encoding(one hot/dummy), binning, clustering, feature selection. These are techniques performed on a dataset consisting of Californian House Prices.
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Apr 1, 2024 - Jupyter Notebook
Code templates for different ML algorithms
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Sep 17, 2020 - R
Open source machine learning library with various machine learning tools
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Jul 27, 2022 - Python
Weight of Evidence Encoding & Information Value
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Apr 7, 2020 - Python
Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.
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Aug 14, 2023 - Jupyter Notebook
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