one-hot-encode | Topic | Ecosyste.ms: Repos

Topic: "one-hot-encode"

aditya9211/SVHN-CNN

Google Street View House Number(SVHN) Dataset, and classifying them through CNN

Language: Jupyter Notebook - Size: 1.02 MB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 58 - Forks: 34

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.

Language: Python - Size: 442 KB - Last synced at: 6 months ago - Pushed at: over 6 years ago - Stars: 34 - Forks: 15

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

Language: Jupyter Notebook - Size: 743 KB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 30 - Forks: 16

timeamagyar/kdd-cup-99-python

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

Language: Jupyter Notebook - Size: 852 KB - Last synced at: almost 2 years ago - Pushed at: about 5 years ago - Stars: 21 - Forks: 12

dimgold/Artificial_Curiosity

Adaptive Reinforcement Learning of curious AI basketball agents

Language: Jupyter Notebook - Size: 14.2 MB - Last synced at: about 2 years ago - Pushed at: over 7 years ago - Stars: 14 - Forks: 6

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.

Language: Python - Size: 16.3 MB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 13 - Forks: 5

madhavkhoslaa/Pytorch-U-Net-Segmentation

Semantic Segmentation Using U-Net Architecture

Language: Jupyter Notebook - Size: 309 KB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 12 - Forks: 4

scruel/campusQA 📦

Deeplearning4J框架搭建的第一个问答小AI

Language: Java - Size: 1.62 MB - Last synced at: 6 days ago - Pushed at: over 7 years ago - Stars: 11 - Forks: 11

gyunggyung/Keras-Applications

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

Size: 348 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 9 - Forks: 7

pemagrg1/one-hot-encoding

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

Language: Python - Size: 8.79 KB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 5 - Forks: 1

petermchale/predict_customer_response

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

Language: Jupyter Notebook - Size: 1.28 MB - Last synced at: almost 2 years ago - Pushed at: about 7 years ago - Stars: 5 - Forks: 3

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

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

Language: Python - Size: 72.3 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 1

avinashsai/Character-level-CNN

Implementation of Character level CNN

Language: Python - Size: 478 KB - Last synced at: about 2 years ago - Pushed at: about 6 years ago - Stars: 2 - Forks: 1

ocramz/record-encode

Generic encoding of record types

Language: Haskell - Size: 39.1 KB - Last synced at: 24 days ago - Pushed at: over 6 years ago - Stars: 2 - Forks: 1

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.

Language: Jupyter Notebook - Size: 2.27 MB - Last synced at: about 2 years ago - Pushed at: almost 8 years ago - Stars: 2 - Forks: 4

RazHoshia/unofficial_encoders

Unofficial but extremely useful Label and One Hot encoders.

Language: Python - Size: 80.1 KB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0

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.

Language: Jupyter Notebook - Size: 108 KB - Last synced at: about 2 years ago - Pushed at: almost 6 years ago - Stars: 1 - Forks: 0

shreyasbhatia09/Google-Analytics-Customer-Revenue-Prediction

Kaggle Challenge

Language: Jupyter Notebook - Size: 449 KB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 0

junaidfiaz143/Recurrent-NeuralNetwork

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

Language: Jupyter Notebook - Size: 12.8 MB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 0

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.

Language: Jupyter Notebook - Size: 1.04 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 1

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.

Language: Jupyter Notebook - Size: 602 KB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 1 - Forks: 0

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