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.
About this Course
Skills you will gain
- 5 stars57.14%
- 4 stars25.39%
- 3 stars7.93%
- 2 stars4.12%
- 1 star5.39%
TOP REVIEWS FROM MACHINE LEARNING FOR DATA ANALYSIS
Good introduction with python example for famous algorithm such as random forest and k-mean
More Implementation oriented and less math
also contains distracting background videos when explaining important concepts
More examples in coding and results are expected. So it is more convenient for students to compare different results and understand deeper
There is some problems because of changes both in SAS and Python after creating the course
About the Data Analysis and Interpretation Specialization
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