Data Science: Supervised Machine Learning in Python
Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Scikit-Learn
4.75 (3533 reviews)
25,484
students
6.5 hours
content
Mar 2025
last update
$29.99
regular price
What you will learn
Understand and implement K-Nearest Neighbors in Python
Understand the limitations of KNN
User KNN to solve several binary and multiclass classification problems
Understand and implement Naive Bayes and General Bayes Classifiers in Python
Understand the limitations of Bayes Classifiers
Understand and implement a Decision Tree in Python
Understand and implement the Perceptron in Python
Understand the limitations of the Perceptron
Understand hyperparameters and how to apply cross-validation
Understand the concepts of feature extraction and feature selection
Understand the pros and cons between classic machine learning methods and deep learning
Use Sci-Kit Learn
Implement a machine learning web service
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944014
udemy ID
8/29/2016
course created date
10/17/2019
course indexed date
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