Training an ML Model
Build your first machine learning model in Azure.
We'll cover the following
Model overview
-
Dataset: We will use the classic
iris.csv
dataset as input. The dataset has six columns with various flower features. The model classifies them into one flower species. -
Training model: We will use
for classification in this lesson.SVM Support Vector Machine
We need two critical components for running this job:
job.yml
: This YAML file contains the parameters and input required for running the job.main.py
: This is the actual Python code to run.
The Iris dataset is almost like a “hello world” program for ML.
Let’s look at the data definition.
The file contains sepal_length
, sepal_width
, petal_length
, and petal_width
as the feature columns.
The output column is a categorical attribute of the species name (Iris-versicolor/Iris-virginica/Iris-setosa).
Get hands-on with 1200+ tech skills courses.