Basic ML using Sklearn to save/load a model, split training & test dataset, create dummy variables and one hot encoder
-
Updated
Sep 9, 2019 - Jupyter Notebook
Basic ML using Sklearn to save/load a model, split training & test dataset, create dummy variables and one hot encoder
AIND Jupyter Notebook to predict student admissions using Keras Neural Networks
Different types of word embedding for text processing
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.
Using random forest to predict Titanic passenger survival.
Trabalho Prático 02 da disciplina de Sistemas de Recomendação.
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.
Kaggle Challenge
This is the code for "Recurrent NeuralNetwork using keras and numpy" By M.Junaid Fiaz
Unofficial but extremely useful Label and One Hot encoders.
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.
Implementation of Character level CNN
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.
Determining the housing prices of California properties for new sellers and also for buyers to estimate the profitability of the deal.
Generic encoding of record types
Customer churn analysis for a telecommunication company
To predict whether booked appointment will be completed or it will be no show.
one hot encoding using numpy, sklearn, and keras. Created Date: 7 Jan 2019
Machine-learning models to predict whether customers respond to a marketing campaign
Add a description, image, and links to the one-hot-encode topic page so that developers can more easily learn about it.
To associate your repository with the one-hot-encode topic, visit your repo's landing page and select "manage topics."