10 Machine Learning Algorithms to Know in 2025
January 28, 2025
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This course is part of Machine Learning: Algorithms in the Real World Specialization
Instructor: Anna Koop
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This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this course will introduce you to problem definition and data preparation in a machine learning project.
By the end of the course, you will be able to clearly define a machine learning problem using two approaches. You will learn to survey available data resources and identify potential ML applications. You will learn to take a business need and turn it into a machine learning application. You will prepare data for effective machine learning applications. This is the first course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute.
This week, you will learn about what machine learning (ML) actually is, contrast different problem scenarios, and explore some common misconceptions about ML. You will apply this knowledge by identifying different components essential to a machine learning business solution.
12 videos6 readings2 assignments3 discussion prompts
This week, you will learn how to translate a business need into a machine learning problem. We'll walk through some applied examples so you can get a feel for what makes a well-defined question for your QuAM. Narrowing down your question and making sure you have the data necessary to learn is critical to ML success!
8 videos4 readings1 assignment2 discussion prompts
This week is all about data. You will learn about data acquisition and understand the various sources of training data. We'll talk about how much data you need and what pitfalls might arise, including ethical issues.
9 videos2 readings1 assignment2 discussion prompts
This week you will learn about the Machine Learning Process Lifecycle (MLPL). After understanding the definitions and components of the MLPL you will analyze the application of the MLPL on a case study.
7 videos2 readings1 assignment2 discussion prompts
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
The Alberta Machine Intelligence Institute (Amii) is home to some of the world’s top talent in machine intelligence. We’re an Alberta-based research institute that pushes the bounds of academic knowledge and guides business understanding of artificial intelligence and machine learning.
Duke University
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Alberta Machine Intelligence Institute
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Amazon Web Services
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Reviewed on Nov 12, 2020
An excellent introduction to the mechanics of ML. Not so deep that coding is required, but simultaneously not so high-level as to be abstract. A very nice intro - thanks for this!
Reviewed on Apr 2, 2022
I loved the way the course was structured, as it gave a very good introduction. The instructor was clear and concise during lectures.
Reviewed on Jan 24, 2020
The course was a really good one introducing you to the machine learning and how you should think and approach an ML problem.
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