Prerequisites:
No experience required
Intro to Machine Learning
Course
Last Updated March 8, 2022
Last Updated March 8, 2022
Prerequisites:
No experience required
Course Lessons
Lesson 1
Intro
An introduction to what you'll learn in this course!
Lesson 2
Linear Regression
Learn how effective linear regression algorithms are in predicting numerical data
Lesson 3
Logistic Regression
Learn about one of the most basic forms of regression modeling - logistic regression
Lesson 4
Decision Trees
Learn how decision trees are a structure for decision-making where each decision leads to a set of consequences or additional decisions.
Lesson 5
Naive Bayes
Learn how powerful Naive Bayesian Algorithms are for creating classifiers for incoming labeled data.
Lesson 6
Support Vector Machines
Learn about how support vector machines can be effective models for classification.
Lesson 7
Ensemble Methods
Learn about bagging and boosting, two common ensemble methods for improving the accuracy of supervised learning approaches.
Lesson 8
Outro
Let's recap and wrap up what we've learned.
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