Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering. By completing this course, you will learn how to apply, test, and interpret machine learning algorithms as alternative methods for addressing your research questions.
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Wesleyan University, founded in 1831, is a diverse, energetic liberal arts community where critical thinking and practical idealism go hand in hand. With our distinctive scholar-teacher culture, creative programming, and commitment to interdisciplinary learning, Wesleyan challenges students to explore new ideas and change the world. Our graduates go on to lead and innovate in a wide variety of industries, including government, business, entertainment, and science.
- 5 stars56.86%
- 4 stars25.55%
- 3 stars7.98%
- 2 stars4.15%
- 1 star5.43%
MACHINE LEARNING FOR DATA ANALYSIS의 최상위 리뷰
Clear and explanatory approach to the object. Instructors have great teaching transmissibility.
More Implementation oriented and less math also contains distracting background videos when explaining important concepts
I enjoyed this course a lot. It's easy and I've learnt what I need to apply the machine learning techniques. Easy and simple. You don't need to be a mathematician.
Good introduction with python example for famous algorithm such as random forest and k-mean
Data Analysis and Interpretation 특화 과정 정보
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.
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