Offered By: IBM

Classify recipe text to cuisine using NLP and Logistic Regre

Have you ever wondered why certain foods taste the way they do? Well, in this project, we will use NLP (Natural Language Processing) to determine the country of origin of recipes using the ingredients. This project will introduce you to NLP and the logistic regression algorithm. NLP is a fantastic field with many applications, but we'll focus on a straightforward beginner project in this guided project. Here we will create a document term matrix (aka term-frequency matrix) using our recipes ingredients and plugging it into a logistic regression model to predict the county of origin.

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At a Glance

Have you ever wondered why certain foods taste the way they do? Well, in this project, we will use NLP (Natural Language Processing) to determine the country of origin of recipes using the ingredients. This project will introduce you to NLP and the logistic regression algorithm. NLP is a fantastic field with many applications, but we'll focus on a straightforward beginner project in this guided project. Here we will create a document term matrix (aka term-frequency matrix) using our recipes ingredients and plugging it into a logistic regression model to predict the county of origin.

Why do this Guided Project

This guided project will give you a high level introduction into how exactly logistic regression works using a simple example. We will also introduce simple NLP concepts in this guided project, giving you exposure and an opportunity to learn about how you can represent a document as a vector of terms (words). Using these tools, you'll be equipped to tackle many other machine learning projects and dive deeper into the NLP field and supervised classification.

A Look at the Project Ahead

Tell your audience what they can expect to learn. Better yet, tell them what they will be able to do as a result of completing your project:
  • Explain how logistic regression works
  • Create and utilize document-term/term-frequency matrices in NLP tasks
  • Perform various optimization techniques to improve model performance in any application

What You'll Need

Your curiosity! This lab will provide you with all the intuitive background you need in order to understand and learn the concepts we use. In terms of coding, just a simple understanding of Python and the Numpy/Pandas libraries is enough. If you aren't familiar with these libraries, Google is your best friend. Everything here is run through your browser in a Jupyter Notebook Environment, so no need to install anything!

Your Instructor

Richard Ye is the author of this guided project. He studied Finance and Statistics at the University of Toronto, and has research experience in financial applications of NLP, and the educational impact of COVID and online learning.

Estimated Effort

1 hour

Level

Beginner

Skills You Will Learn

Python, Data Science, Machine Learning, NLP, Embeddable AI

Language

English

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Instructors

Profile picture for Richard Ye

Richard Ye

Skills Network Data Scientist

A student of statistics interested in Machine Learning, Deep Learning (NLP specifically) and software development.

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