Compare Models with Experiments in Azure ML Studio
Did you know that you can compare models in Azure Machine Learning? In this 1-hour project-based course, you will learn how to log plots in experiments, log numeric metrics in experiments and visualize metrics in Azure Machine Learning Studio. To achieve this, we will use one example data, train a couple of machine learning algorithms in Jupyter notebook and visualize their results in Azure Machine Learning Studio Portal interface. In order to be successful in this project, you will need knowledge of Python language and experience with machine learning in Python.
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- Level Beginner
- Duration 4 hours
- Course by Coursera Project Network
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Did you know that you can compare models in Azure Machine Learning? In this 1-hour project-based course, you will learn how to log plots in experiments, log numeric metrics in experiments and visualize metrics in Azure Machine Learning Studio. To achieve this, we will use one example data, train a couple of machine learning algorithms in Jupyter notebook and visualize their results in Azure Machine Learning Studio Portal interface. In order to be successful in this project, you will need knowledge of Python language and experience with machine learning in Python. Also, Azure subscription is required (free trial is an option for those who don't have it), as well as Azure Machine Learning resource and a compute instance within. Instructional links will be provided to guide you through creation, if needed, in the first task. If you are ready to make your experience training models simpler and more enjoyable, this is a course for you! Let's get started!Modules
Your Learning Journey
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Assignment
- Assess Your Knowledge
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- Compare Models with Experiments in Azure ML Studio
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- Project Overview
Auto Summary
Unlock the power of model comparison in Azure Machine Learning with this engaging course designed for beginners in IT and Computer Science. In just one hour, this project-based learning experience will teach you to log plots and numeric metrics in experiments as well as visualize these metrics within the Azure Machine Learning Studio. Guided by hands-on examples, you will train various machine learning algorithms using Jupyter notebooks and analyze their performance through Azure's intuitive portal interface. Essential prerequisites include a working knowledge of Python and prior experience with machine learning in Python. Additionally, you will need an Azure subscription, which can be set up for free, along with an Azure Machine Learning resource and compute instance. The course provides all necessary links and guidance to help you set up your environment, ensuring you can start learning right away. Brought to you by Coursera, this free course offers a streamlined and enjoyable way to enhance your model training capabilities. If you're eager to simplify your machine learning workflow and enhance your skills in model comparison, this course is perfect for you. Dive in and start your journey today!
Laura Ramov