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Ryan Ahmed
Hello everyone and welcome to this new hands-on project on Machine Learning Regression with Amazon Web Services (AWS) AutoGluon.
Read more
Hello everyone and welcome to this new hands-on project on Machine Learning Regression with Amazon Web Services (AWS) AutoGluon.
Read more
Hello everyone and welcome to this new hands-on project on Machine Learning Regression with Amazon Web Services (AWS) AutoGluon.
In this project, we will train several regression models using a super powerful library known as AutoGluon. AutoGluon is the library behind AWS SageMaker autopilot and it allows for quick prototyping of several powerful models using a few lines of code.
Register for this course and see more details by visiting:
OpenCourser.com/course/ssnwv5/solving
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What's inside
Syllabus
Project Overview
Hello everyone and welcome to this new hands-on project on Machine Learning Regression with AWS AutoGluon. In this project, we will train several regression models using a super powerful library known as AutoGluon. AutoGluon is the library behind Amazon web services SageMaker autopilot and it allows for quick prototyping of several powerful models using a few lines of code.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops expertise in regression models, a core skill in machine learning, which is required for several roles in tech and scientific industries
Provides practical experience with Amazon Web Services, a widely used cloud platform for machine learning
Harnessing the power of AutoGluon, an advanced library that makes machine learning more accessible
Ideal for individuals seeking to enhance their understanding of machine learning algorithms, specifically in regression tasks
Prerequisites may be necessary as the course assumes familiarity with foundational machine learning concepts
Presumes a certain level of coding proficiency, particularly in Python
Save this course
Save Solving ML Regression Problems with AWS AutoGluon 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 Solving ML Regression Problems with AWS AutoGluon with these
activities:
Review Statistics
Show steps
Will help refresh your understanding of basic statistical concepts and techniques.
Browse courses on
Data Analysis
Show steps
-
Revisit key concepts such as descriptive statistics, probability distributions, sampling distributions, and hypothesis testing.
-
Practice solving solved examples to understand the application of statistical methods.
Explore AWS AutoGluon Documentation
Show steps
Helps enhance your understanding of AutoGluon's functionalities and its usage in building regression models.
Show steps
-
Visit the official AWS AutoGluon documentation website and explore the available tutorials.
-
Follow the step-by-step guides to learn about the different features and capabilities of AutoGluon for regression tasks.
Participate in Online Discussion Forums
Show steps
Provides opportunities to engage with fellow learners, share insights, and get clarifications on course topics.
Show steps
-
Join online discussion forums or platforms relevant to the course.
-
Actively participate in discussions, asking thoughtful questions and providing helpful responses to others.
Three other activities
Expand to see all activities and additional details
Show all six activities
Solve Regression Practice Problems
Show steps
Provides hands-on experience in solving regression problems and testing your understanding of the concepts.
Show steps
-
Find online resources or textbooks that provide regression practice problems.
-
Attempt to solve the problems on your own, using the concepts and techniques learned in the course.
-
Check your solutions against the provided answer key or consult with the course instructor if needed.
Develop a Regression Model for a Real-World Problem
Show steps
Allows you to apply your knowledge to a practical scenario, reinforcing your understanding of regression modeling.
Show steps
-
Identify a real-world problem that can be addressed using regression analysis.
-
Collect and prepare the relevant data for your analysis.
-
Use AutoGluon to build and evaluate different regression models for the problem.
-
Interpret the results of your analysis and make predictions based on the developed model.
Mentor Junior Learners
Show steps
Enhances your understanding of the concepts while fostering empathy and leadership qualities.
Show steps
-
Identify opportunities to mentor junior learners who are struggling with the course material.
-
Provide guidance, support, and encouragement to these learners, helping them overcome challenges and reach their learning goals.
Review Statistics
Show steps
Will help refresh your understanding of basic statistical concepts and techniques.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Revisit key concepts such as descriptive statistics, probability distributions, sampling distributions, and hypothesis testing.
- Practice solving solved examples to understand the application of statistical methods.
Explore AWS AutoGluon Documentation
Show steps
Helps enhance your understanding of AutoGluon's functionalities and its usage in building regression models.
Show steps
Show steps
Show steps
- Visit the official AWS AutoGluon documentation website and explore the available tutorials.
- Follow the step-by-step guides to learn about the different features and capabilities of AutoGluon for regression tasks.
Participate in Online Discussion Forums
Show steps
Provides opportunities to engage with fellow learners, share insights, and get clarifications on course topics.
Show steps
Show steps
Show steps
- Join online discussion forums or platforms relevant to the course.
- Actively participate in discussions, asking thoughtful questions and providing helpful responses to others.
Three other activities
Expand to see all activities and additional details
Show all six activities
Solve Regression Practice Problems
Show steps
Provides hands-on experience in solving regression problems and testing your understanding of the concepts.
Show steps
Show steps
Show steps
- Find online resources or textbooks that provide regression practice problems.
- Attempt to solve the problems on your own, using the concepts and techniques learned in the course.
- Check your solutions against the provided answer key or consult with the course instructor if needed.
Develop a Regression Model for a Real-World Problem
Show steps
Allows you to apply your knowledge to a practical scenario, reinforcing your understanding of regression modeling.
Show steps
Show steps
Show steps
- Identify a real-world problem that can be addressed using regression analysis.
- Collect and prepare the relevant data for your analysis.
- Use AutoGluon to build and evaluate different regression models for the problem.
- Interpret the results of your analysis and make predictions based on the developed model.
Mentor Junior Learners
Show steps
Enhances your understanding of the concepts while fostering empathy and leadership qualities.
Show steps
Show steps
Show steps
- Identify opportunities to mentor junior learners who are struggling with the course material.
- Provide guidance, support, and encouragement to these learners, helping them overcome challenges and reach their learning goals.
Career center
Learners who complete Solving ML Regression Problems with AWS AutoGluon will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. This course provides a solid foundation in machine learning regression techniques, which are essential for building accurate and reliable models. By learning how to apply these techniques using AWS AutoGluon, you will gain the skills necessary to succeed in this in-demand field.
Data Scientist
Data Scientist
Data Scientists use machine learning and other advanced analytical techniques to extract insights from data. This course provides a comprehensive overview of machine learning regression, which is a fundamental skill for Data Scientists. By learning how to use AWS AutoGluon to train and evaluate regression models, you will gain a competitive edge in this highly competitive field.
Data Analyst
Data Analyst
Data Analysts use data to solve business problems. This course provides a strong foundation in machine learning regression, which is a powerful tool for analyzing and predicting trends. By learning how to apply these techniques using AWS AutoGluon, you will gain the skills necessary to make data-driven decisions and drive business value.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course provides a solid foundation in machine learning regression, which is becoming increasingly important for building intelligent software applications. By learning how to use AWS AutoGluon to train and deploy regression models, you will gain the skills necessary to stay competitive in this rapidly evolving field.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course provides a comprehensive overview of machine learning regression, which is a powerful tool for building predictive models. By learning how to use AWS AutoGluon to train and evaluate regression models, you will gain the skills necessary to succeed in this challenging and rewarding field.
Business Analyst
Business Analyst
Business Analysts use data to solve business problems. This course provides a strong foundation in machine learning regression, which is a valuable tool for analyzing and predicting trends. By learning how to apply these techniques using AWS AutoGluon, you will gain the skills necessary to make data-driven decisions and drive business value.
Product Manager
Product Manager
Product Managers are responsible for developing and launching new products. This course provides a solid foundation in machine learning regression, which is becoming increasingly important for building data-driven products. By learning how to use AWS AutoGluon to train and deploy regression models, you will gain the skills necessary to stay competitive in this rapidly evolving field.
Consultant
Consultant
Consultants provide advice and guidance to businesses on a variety of topics. This course provides a comprehensive overview of machine learning regression, which is a powerful tool for analyzing data and making predictions. By learning how to use AWS AutoGluon to train and evaluate regression models, you will gain the skills necessary to provide valuable insights to your clients.
Researcher
Researcher
Researchers conduct original research in a variety of fields. This course provides a solid foundation in machine learning regression, which is a powerful tool for analyzing data and testing hypotheses. By learning how to use AWS AutoGluon to train and evaluate regression models, you will gain the skills necessary to make significant contributions to your field.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This course provides a comprehensive overview of machine learning regression, which is a powerful tool for building predictive models. By learning how to use AWS AutoGluon to train and evaluate regression models, you will gain the skills necessary to succeed in this challenging and rewarding field.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk. This course provides a solid foundation in machine learning regression, which is becoming increasingly important for building accurate and reliable risk models. By learning how to use AWS AutoGluon to train and deploy regression models, you will gain the skills necessary to stay competitive in this rapidly evolving field.
Financial Analyst
Financial Analyst
Financial Analysts use data to analyze and make recommendations on investments. This course provides a solid foundation in machine learning regression, which is becoming increasingly important for building predictive models. By learning how to use AWS AutoGluon to train and deploy regression models, you will gain the skills necessary to stay competitive in this rapidly evolving field.
Economist
Economist
Economists study the production, distribution, and consumption of goods and services. This course provides a solid foundation in machine learning regression, which is becoming increasingly important for building models to predict economic trends. By learning how to use AWS AutoGluon to train and deploy regression models, you will gain the skills necessary to stay competitive in this rapidly evolving field.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. This course provides a solid foundation in machine learning regression, which is becoming increasingly important for building models to optimize business operations. By learning how to use AWS AutoGluon to train and deploy regression models, you will gain the skills necessary to stay competitive in this rapidly evolving field.
Risk Manager
Risk Manager
Risk Managers identify, assess, and mitigate risks. This course provides a solid foundation in machine learning regression, which is becoming increasingly important for building models to predict and manage risks. By learning how to use AWS AutoGluon to train and deploy regression models, you will gain the skills necessary to stay competitive in this rapidly evolving field.
For more career information including salaries, visit:
OpenCourser.com/course/ssnwv5/solving
Reading list
We've selected ten 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
Solving ML Regression Problems with AWS AutoGluon.
A comprehensive overview of statistical learning, this book covers a wide range of topics, including regression, classification, and clustering. It valuable resource for anyone who wants to learn more about the field.
A comprehensive guide to regression modeling, this book covers a wide range of topics, including linear regression, logistic regression, and survival analysis. It valuable resource for anyone who wants to learn more about regression modeling.
A comprehensive overview of the mathematical foundations of machine learning, this book valuable resource for anyone who wants to learn more about the field. It covers a wide range of topics, including linear algebra, calculus, and probability.
A practical guide to machine learning in R, this book covers a variety of topics, including regression, classification, and clustering. It valuable resource for anyone who wants to learn more about how to apply machine learning to real-world problems.
Save
Provides an overview of the most popular regression modeling techniques, this book can serve as a useful companion to this course. It begins with a discussion of simple linear regression and then introduces more advanced techniques such as. It also covers model evaluation and selection.
A practical guide to machine learning in Python, this book covers a variety of topics, including regression, classification, and clustering. It valuable resource for anyone who wants to learn more about how to apply machine learning to real-world problems.
Provides a solid foundation in statistical modeling, this book covers a variety of topics, including regression, analysis of variance, and non-parametric methods. It valuable resource for anyone who wants to learn more about the theoretical underpinnings of regression modeling.
Companion book to the popular machine learning MOOC of the same name, a good background in probability and linear algebra will be useful. covers a wide range of machine learning topics, including regression, and valuable resource for anyone interested in learning more about the field.
A practical guide to deep learning in Python, this book covers a variety of topics, including regression, classification, and natural language processing. It valuable resource for anyone who wants to learn more about how to apply deep learning to real-world problems.
Focuses primarily on how to use data mining to improve business intelligence, this book covers a variety of topics relevant to regression, including data preparation, model selection, and evaluation. It also provides case studies to illustrate how data mining techniques can be applied in real-world situations.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ssnwv5/solving
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Language
English
Good to know
Develops expertise in regression models, a core skill in machine learning, which is required for several roles in tech and scientific industries
Provides practical experience with Amazon Web Services, a widely used cloud platform for machine learning
Harnessing the power of AutoGluon, an advanced library that makes machine learning more accessible
Ideal for individuals seeking to enhance their understanding of machine learning algorithms, specifically in regression tasks
Prerequisites may be necessary as the course assumes familiarity with foundational machine learning concepts
Presumes a certain level of coding proficiency, particularly in Python
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