The Nuts and Bolts of Machine Learning All Quiz Answer | Coursera Google Certificate | Course 6
This is the sixth of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll learn about machine learning, which uses algorithms and statistics to teach computer systems to discover patterns in data. Data professionals use machine learning to help analyze large amounts of data, solve complex problems, and make accurate predictions. You’ll focus on the two main types of machine learning: supervised and unsupervised. You'll learn how to apply different machine learning models to business problems and become familiar with specific models such as Naive Bayes, decision tree, random forest, and more.
Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.
By the end of this course, you will:
-Apply feature engineering techniques using Python
-Construct a Naive Bayes model
-Describe how unsupervised learning differs from supervised learning
-Code a K-means algorithm in Python
-Evaluate and optimize the results of K-means model
-Explore decision tree models, how they work, and their advantages over other types of supervised machine learning
-Characterize bagging in machine learning, specifically for random forest models
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Course 1 • Foundations of Data Science Quiz Answers |...
Course 2 • Get Started with Python All Quiz Answers |...
Course 3 • Go Beyond the Numbers Translate Data into ...
Course 4 • The Power of Statistics All Quiz Answer | ...
Course 5 • Regression Analysis Simplify Complex Data ...
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