Data Science: Supervised Machine Learning in Python

Data Science: Supervised Machine Learning in Python, Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Sci-Kit Learn

• Created by Lazy Programmer Inc.
•  English
•  English [Auto-generated], Spanish [Auto-generated]

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What you'll 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

Includes

• 6 hours on-demand video
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion