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.
本课程是 Machine Learning: Algorithms in the Real World 专项课程 专项课程的一部分
Introduction to Applied Machine Learning
提供方
学习Course的学生是
- Data Scientists
- Machine Learning Engineers
- Chief Technology Officers (CTOs)
- Vice Presidents
- Researchers
教学大纲 - 您将从这门课程中学到什么
Introduction to Machine Learning Applications
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.
Machine Learning in the Real World
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!
Learning Data
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.
Machine Learning Projects
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.
来自Introduction to Applied Machine Learning的热门评论
This course will give the actual understanding especially focusing on different types of Machine learning with real examples. I'm so excited to learn more about it.
I enjoyed this course. It was a good refresher but I believe that it is also good for people that want to understand this Machine Learning hype...
讲师
Anna Koop
Senior Scientific Advisor关于 Alberta Machine Intelligence Institute
关于 Machine Learning: Algorithms in the Real World 专项课程
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