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Laura Ramov
Did you know that you can compare models in Azure Machine Learning?
Read more
Did you know that you can compare models in Azure Machine Learning?
Read more
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!
Register for this course and see more details by visiting:
OpenCourser.com/course/btjbaf/compare
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What's inside
Syllabus
Project Overview
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. You will use those skills to compare machine learning models and choose the best one for your problem.
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.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
This project-based course is designed for individuals with knowledge of Python and experience in machine learning in Python
Teaches how to log plots in experiments, log numeric metrics in experiments and visualize metrics in Azure Machine Learning Studio
Suitable for learners interested in comparing machine learning models and choosing the best one for their problem
Save this course
Save Compare Models with Experiments in Azure ML Studio to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Compare Models with Experiments in Azure ML Studio with these
activities:
Attend Azure User Group meetings
Show steps
Provides opportunities to connect with other Azure users, learn about best practices, and stay updated on the latest Azure technologies
Browse courses on
Networking
Show steps
-
Find a local Azure User Group
-
Attend monthly meetings to network and learn from other Azure users
Review of Python programming basics
Show steps
Strengthens foundational knowledge in Python programming, which is essential for working with Azure Machine Learning
Browse courses on
Python
Show steps
-
Review basic Python syntax and data structures
-
Practice writing simple Python scripts
Review of machine learning concepts
Show steps
Refreshes key machine learning concepts, ensuring a solid understanding before delving into Azure Machine Learning
Browse courses on
Machine Learning
Show steps
-
Review supervised and unsupervised learning algorithms
-
Practice implementing simple machine learning models
Four other activities
Expand to see all activities and additional details
Show all seven activities
Compilation of resources on Azure Machine Learning
Show steps
Provides a curated collection of resources to support learning and exploration of Azure Machine Learning
Browse courses on
Azure Machine Learning
Show steps
-
Gather links to useful tutorials, articles, and documentation on Azure Machine Learning
-
Organize resources into categories such as beginner-friendly, advanced, and specific topics
-
Share the compilation with other students or interested parties
Tutorial on visualizing metrics in Azure Machine Learning Studio
Show steps
Provides practical experience in visualizing metrics in Azure Machine Learning Studio
Browse courses on
Metrics
Show steps
-
Open Azure Machine Learning Studio
-
Connect to an Azure Machine Learning workspace
-
Explore the visualization options for different types of metrics
Practice logging plots in experiments
Show steps
Reinforces understanding of how to log plots in Azure Machine Learning experiments
Browse courses on
Metrics
Show steps
-
Create a new Azure Machine Learning experiment
-
Load a dataset and train a machine learning model
-
Log a plot of the model's performance
Practice logging numeric metrics in experiments
Show steps
Enhances understanding of how to log numeric metrics in Azure Machine Learning experiments
Browse courses on
Metrics
Show steps
-
Create a new Azure Machine Learning experiment
-
Load a dataset and train a machine learning model
-
Log a numeric metric of the model's performance
Attend Azure User Group meetings
Show steps
Provides opportunities to connect with other Azure users, learn about best practices, and stay updated on the latest Azure technologies
Browse courses on
Networking
Show steps
Show steps
Show steps
- Find a local Azure User Group
- Attend monthly meetings to network and learn from other Azure users
Review of Python programming basics
Show steps
Strengthens foundational knowledge in Python programming, which is essential for working with Azure Machine Learning
Browse courses on
Python
Show steps
Show steps
Show steps
- Review basic Python syntax and data structures
- Practice writing simple Python scripts
Review of machine learning concepts
Show steps
Refreshes key machine learning concepts, ensuring a solid understanding before delving into Azure Machine Learning
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Review supervised and unsupervised learning algorithms
- Practice implementing simple machine learning models
Four other activities
Expand to see all activities and additional details
Show all seven activities
Compilation of resources on Azure Machine Learning
Show steps
Provides a curated collection of resources to support learning and exploration of Azure Machine Learning
Browse courses on
Azure Machine Learning
Show steps
Show steps
Show steps
- Gather links to useful tutorials, articles, and documentation on Azure Machine Learning
- Organize resources into categories such as beginner-friendly, advanced, and specific topics
- Share the compilation with other students or interested parties
Tutorial on visualizing metrics in Azure Machine Learning Studio
Show steps
Provides practical experience in visualizing metrics in Azure Machine Learning Studio
Browse courses on
Metrics
Show steps
Show steps
Show steps
- Open Azure Machine Learning Studio
- Connect to an Azure Machine Learning workspace
- Explore the visualization options for different types of metrics
Practice logging plots in experiments
Show steps
Reinforces understanding of how to log plots in Azure Machine Learning experiments
Browse courses on
Metrics
Show steps
Show steps
Show steps
- Create a new Azure Machine Learning experiment
- Load a dataset and train a machine learning model
- Log a plot of the model's performance
Practice logging numeric metrics in experiments
Show steps
Enhances understanding of how to log numeric metrics in Azure Machine Learning experiments
Browse courses on
Metrics
Show steps
Show steps
Show steps
- Create a new Azure Machine Learning experiment
- Load a dataset and train a machine learning model
- Log a numeric metric of the model's performance
Career center
Learners who complete Compare Models with Experiments in Azure ML Studio will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer uses Azure ML Studio to build and deploy machine learning models. This course on comparing models with experiments will help in this area by teaching how to log plots and metrics from experiments in Azure ML Studio. This is a useful technique for a Machine Learning Engineer to know.
Data Analyst
Data Analyst
A Data Analyst may use Azure ML Studio in their day-to-day work. This course is useful to a Data Analyst because it teaches them how to use Azure ML Studio to log plots and metrics from experiments, then visualize them. This is a valuable skill that can help a Data Analyst gain actionable insights from data.
Data Scientist
Data Scientist
A Data Scientist may be involved with advanced visualization of data in their work. This course on comparing models with experiments using Azure ML Studio would fit well into the skillset required by this career, as an individual will learn how to log plots and metrics from experiments in Azure ML Studio. This is a relevant skill for a Data Scientist.
Data Engineer
Data Engineer
A Data Engineer may use Azure ML Studio to build and manage data pipelines for machine learning models. This course may be useful to a Data Engineer because it teaches them how to log plots and metrics from experiments in Azure ML Studio. This is a valuable skill for a Data Engineer to have.
Cloud Engineer
Cloud Engineer
A Cloud Engineer may use Azure ML Studio to build and manage cloud-based machine learning solutions. This course on comparing models with experiments may be useful to a Cloud Engineer by teaching them how to log plots and metrics from experiments in Azure ML Studio. This skill is a part of a Cloud Engineer's responsibilities.
Data Science Consultant
Data Science Consultant
A Data Science Consultant may use Azure ML Studio to build and manage data science solutions for clients. This course may be useful by teaching how to log plots and metrics from experiments in Azure ML Studio, which is a skill used in consulting.
Business Analyst
Business Analyst
A Business Analyst may use Azure ML Studio to build and manage machine learning solutions for business problems. This course can be helpful to a Business Analyst by teaching them how to log plots and metrics from experiments in Azure ML Studio. This can assist them in communicating the results of machine learning models to stakeholders.
Software Engineer
Software Engineer
A Software Engineer may use Azure ML Studio for a variety of tasks, including building and deploying machine learning models. This course will be of help to a Software Engineer because it teaches them how to log plots and metrics from experiments in Azure ML Studio. This is a skill that can contribute to success in this field.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst may use Azure ML Studio to build and manage quantitative models. This course on comparing models with experiments may be beneficial to a Quantitative Analyst because it teaches them how to log plots and metrics from experiments in Azure ML Studio.
Statistician
Statistician
A Statistician may use Azure ML Studio to build and manage statistical models. This course on comparing models with experiments may be of some help to a Statistician, as it teaches them how to log plots and metrics from experiments in Azure ML Studio.
Product Manager
Product Manager
A Product Manager may use Azure ML Studio to build and manage machine learning products. This course on comparing models with experiments may be useful to a Product Manager because it teaches them how to log plots and metrics from experiments in Azure ML Studio. This is a skill that can help a Product Manager understand the performance of machine learning models.
Financial Analyst
Financial Analyst
A Financial Analyst may use Azure ML Studio to build and manage financial models. This course may be useful by teaching a Financial Analyst how to log plots and metrics from experiments in Azure ML Studio.
Risk Analyst
Risk Analyst
A Risk Analyst may use Azure ML Studio to build and manage risk models. This course on comparing models with experiments is somewhat relevant to this profession, as it teaches how to log plots and metrics from experiments in Azure ML Studio.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst may use Azure ML Studio to build and manage operations research models. This course on comparing models with experiments is not a great fit, but it may be useful.
Actuary
Actuary
An Actuary may use Azure ML Studio to build and manage actuarial models. This course on comparing models with experiments is not a great fit, but it may be useful to learn how to log plots and metrics from experiments in Azure ML Studio.
For more career information including salaries, visit:
OpenCourser.com/course/btjbaf/compare
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Compare Models with Experiments in Azure ML Studio.
Provides a practical guide to machine learning using Azure. It covers the basics of machine learning, as well as how to use Azure Machine Learning Studio to train and deploy machine learning models.
Provides a comprehensive introduction to deep learning using Python. It covers the fundamentals of deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Provides a practical introduction to machine learning for hackers. It covers the basics of machine learning, as well as how to use Python to train and deploy machine learning models.
Save
Provides a comprehensive introduction to deep learning. It covers the fundamentals of deep learning, as well as advanced topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Provides a comprehensive introduction to statistical learning. It covers the fundamentals of statistical learning, as well as advanced topics such as Bayesian learning and reinforcement learning.
Provides a comprehensive introduction to pattern recognition and machine learning. It covers the fundamentals of pattern recognition, as well as advanced topics such as statistical learning theory and graphical models.
Provides a comprehensive introduction to reinforcement learning. It covers the fundamentals of reinforcement learning, as well as advanced topics such as deep reinforcement learning and multi-agent reinforcement learning.
Provides a probabilistic introduction to machine learning. It covers the fundamentals of probability theory, as well as advanced topics such as Bayesian learning and reinforcement learning.
Provides a comprehensive introduction to statistical learning. It covers the fundamentals of statistical learning, as well as advanced topics such as Bayesian learning and reinforcement learning.
Provides a comprehensive introduction to data science. It covers the fundamentals of data science, as well as how to use Python to clean, analyze, and visualize data.
Provides a comprehensive introduction to machine learning using R. It covers the fundamentals of machine learning, as well as how to use R to train and deploy machine learning models.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/btjbaf/compare
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Effort
1.5 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Laura Ramov
Language
English
Good to know
This project-based course is designed for individuals with knowledge of Python and experience in machine learning in Python
Teaches how to log plots in experiments, log numeric metrics in experiments and visualize metrics in Azure Machine Learning Studio
Suitable for learners interested in comparing machine learning models and choosing the best one for their problem
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