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.
This course is part of the Data Analysis and Interpretation Specialization
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About this Course
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Try Coursera for BusinessSkills you will gain
- Data Analysis
- Python Programming
- Machine Learning
- Exploratory Data Analysis
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Syllabus - What you will learn from this course
Decision Trees
Random Forests
Lasso Regression
K-Means Cluster Analysis
Reviews
- 5 stars57.14%
- 4 stars25.39%
- 3 stars7.93%
- 2 stars4.12%
- 1 star5.39%
TOP REVIEWS FROM MACHINE LEARNING FOR DATA ANALYSIS
More examples in coding and results are expected. So it is more convenient for students to compare different results and understand deeper
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.
Clear and explanatory approach to the object. Instructors have great teaching transmissibility.
I would like to have an opportunity to contact my reviews.
About the Data Analysis and Interpretation Specialization

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