one-hot-encode

mattkearns/automated-data-preprocessing

A command-line utility program for automating the trivial, frequently occurring data preparation tasks: missing value interpolation, outlier removal, and encoding categorical variables.

KwokHing/YandexCatBoost-Python-Demo

Demo on the capability of Yandex CatBoost gradient boosting classifier on a fictitious IBM HR dataset obtained from Kaggle. Data exploration, cleaning, preprocessing and model tuning are performed on the dataset

timeamagyar/kdd-cup-99-python

Analysis and preprocessing of the kdd cup 99 dataset using python and scikit-learn

dimgold/Artificial_Curiosity

Adaptive Reinforcement Learning of curious AI basketball agents

Abhishekmamidi123/NLP

This repository contains Sentiment Classification, Word Level Text Generation, Character Level Text Generation and other important codes/notes on NLP. Python and Keras are used for implementation.

madhavkhoslaa/Pytorch-U-Net-Segmentation

Semantic Segmentation Using U-Net Architecture

scruel/campusQA

Deeplearning4J框架搭建的第一个问答小AI

gyunggyung/Keras-Applications

Keras 응용(CNN, RNN, GAN, DNN, ETC...) 사용법 예시

vishank94/Movie-Recommendation-System

Movie Recommendation System

pemagrg1/one-hot-encoding

one hot encoding using numpy, sklearn, and keras. Created Date: 7 Jan 2019

petermchale/predict_customer_response

Machine-learning models to predict whether customers respond to a marketing campaign

IshtyM/Prediction-of-Shows-and-No-Shows-in-HealthCare-Industry

To predict whether booked appointment will be completed or it will be no show.

SaeidRostami/Customer_Churn

Customer churn analysis for a telecommunication company

abhmalik/categorical-feature-importances-without-one-hot-encoding-dummies

Feature Importance of categorical variables by converting them into dummy variables (One-hot-encoding) can skewed or hard to interpret results. Here I present a method to get around this problem using H2O.

avinashsai/Character-level-CNN

Implementation of Character level CNN

ocramz/record-encode

Generic encoding of record types

sruti-jain/Predicting-House-Prices---Regression

Determining the housing prices of California properties for new sellers and also for buyers to estimate the profitability of the deal.

junaidfiaz143/Recurrent-NeuralNetwork

This is the code for "Recurrent NeuralNetwork using keras and numpy" By M.Junaid Fiaz

ltfschoen/aind2-cnn

north0n-FI/House-Prices-Advanced-Regression-Techniques

This is my contribution to a competition on kaggle.com, where you have a dataset with 79 explanatory variables describing (almost) every aspect of c. 1500 residential homes in Ames, Iowa. The aim is to predict the final price of each home.

RazHoshia/unofficial_encoders

Unofficial but extremely useful Label and One Hot encoders.

rnk20/Neural-Networks

Deep Neural Networks like Single Layer Perceptron and Multi Layer Perceptron implementation using Tensorflow library on Datasets like MNIST and Naval Mine for categorical Classification. Saving and Restoring Tensorflow "Variables" weights for testing.

shreyasbhatia09/Google-Analytics-Customer-Revenue-Prediction

Kaggle Challenge

luizhemelo/SR_TrabalhoPratico02

Trabalho Prático 02 da disciplina de Sistemas de Recomendação.

maryamteimouri/DataAnalysis-and-KnowledgeDiscovery

This project aims to practice the steps of Crisp Data Mining ( CRISP-DM ). The repository includes 3 phases, data understanding, supervised learning, and unsupervised learning.

tebateman/Titanic-Sink-or-Swim

Using random forest to predict Titanic passenger survival.

arynas/kind_of_embeddings

Different types of word embedding for text processing

LintangWisesa/ML_Sklearn_DummyVar_OneHotEncoder

Basic ML using Sklearn to save/load a model, split training & test dataset, create dummy variables and one hot encoder

ltfschoen/aind2-dl

AIND Jupyter Notebook to predict student admissions using Keras Neural Networks