How to do Category encoding and string lookup using keras?
MACHINE LEARNING RECIPES DATA CLEANING PYTHON DATA MUNGING PANDAS CHEATSHEET     ALL TAGS

How to do Category encoding and string lookup using keras?

How to do Category encoding and string lookup using keras?

This recipe helps you do Category encoding and string lookup using keras

0

Recipe Objective

Category encoding and string lookup using keras.

one-hot encoding is the representation of categorical variables as binary vectors.

The keras provides a to_categorical() method. It can encode the strings data into numerical or integer data.

Step 1- Importing Libraries.

from keras.preprocessing.text import one_hot from keras.preprocessing.text import text_to_word_sequence from keras.preprocessing.text import Tokenizer

Step 2- Encoding the text.

Define the text that you want to encode.

#Define text text = 'a book or other written or printed work, regarded in terms of its content rather than its physical form' #Size of the vocabulary words = set(text_to_word_sequence(text)) vocab = len(words)

Step 3- One hot encode the text

# integer encode the document result = one_hot(text, round(vocab_size)) print(result)
[6, 2, 7, 3, 2, 7, 7, 1, 5, 2, 7, 4, 1, 2, 7, 4, 1, 4, 5]

Relevant Projects

Predict Churn for a Telecom company using Logistic Regression
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.

Learn to prepare data for your next machine learning project
Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.

Data Science Project on Wine Quality Prediction in R
In this R data science project, we will explore wine dataset to assess red wine quality. The objective of this data science project is to explore which chemical properties will influence the quality of red wines.

Ecommerce product reviews - Pairwise ranking and sentiment analysis
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.

Zillow’s Home Value Prediction (Zestimate)
Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.

Sequence Classification with LSTM RNN in Python with Keras
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset​ using Keras in Python.

Data Science Project - Instacart Market Basket Analysis
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.

Music Recommendation System Project using Python and R
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.

Forecast Inventory demand using historical sales data in R
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.

Predict Census Income using Deep Learning Models
In this project, we are going to work on Deep Learning using H2O to predict Census income.