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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277 EnrolledAt 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
A Look at the Project Ahead
- 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 Instructor
Estimated Effort
1 hour
Level
Beginner
Skills You Will Learn
Python, Data Science, Machine Learning, NLP, Embeddable AI
Language
English