msb-public
/
ML-For-Beginners
mirror of https://github.com/microsoft/ML-For-Beginners.git
1
0
Code Issues Projects Releases Wiki Activity
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from '8f89f53bd4'
${ noResults }
ML-For-Beginners/4-Classification
History
Jen Looper b7c3a8ba99
Scikit-learn spelling audit 		3 years ago
..
1-Introduction Scikit-learn spelling audit 3 years ago
2-Classifiers-1 Scikit-learn spelling audit 3 years ago
3-Classifiers-2 Scikit-learn spelling audit 3 years ago
4-Applied Scikit-learn spelling audit 3 years ago
data renaming classification content as 'cuisines', not recipes 3 years ago
images lesson details on regions 3 years ago
translations re-numbering lesson groups 4 years ago
README.md renaming classification content as 'cuisines', not recipes 3 years ago

README.md

Getting Started with Classification

Regional topic: Delicious Asian and Indian Cuisines 🍜

In Asia and India, food traditions are extremely diverse, and very delicious! Let's look at data about regional cuisines to try to guess where they originated.

Thai food seller

Photo by Lisheng Chang on Unsplash

What you will learn

In this section, you will build on the skills you learned in Lesson 1 (Regression) to learn about other classifiers you can use that will help you learn about your data.

There are useful low-code tools that can help you learn about working with Classification models. Try Azure ML for this task

Lessons

  1. Introduction to Classification
  2. More Classifiers
  3. Yet Other Classifiers
  4. Applied ML: Build a Web App

Credits

"Getting Started with Classification" was written with ♥️ by Cassie Breviu and Jen Looper

The delicious cuisines dataset was sourced from Kaggle