A repository of exercises to support the training.
In this exercise, you will explore the realm of classification using Azure Machine Learning Designer. Specifically, you will train a classification model to predict whether an individual has diabetes or not based on relevant features.
To deepen your understanding of classification modeling and its application in Azure Machine Learning Designer, we recommend exploring the following module provided by Microsoft Learning:
NOTE: In the link above, the diabetic data is missing. I've copied from somewhere on GitHub. Please use this link instead. Diabetic Data
This module covers a variety of topics including the fundamentals of classification algorithms, techniques for data preprocessing, model training and evaluation, and deployment of classification models in Azure Machine Learning. By completing this module, you'll gain valuable insights into building and deploying classification models for real-world scenarios.
In this exercise, you'll delve into the process of training a classification model in Azure Machine Learning. Using a dataset containing relevant medical information, including features such as glucose levels, blood pressure, and body mass index (BMI), you'll follow a series of steps to preprocess the data, select appropriate features, train the classification model, and evaluate its performance in predicting diabetes.
After completing this exercise, you'll have developed the skills and knowledge necessary to train and deploy classification models in Azure Machine Learning. Stay tuned for upcoming modules where we'll explore advanced machine learning techniques and applications.
Happy modeling!