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All Programs
Computers
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Python
Learning from Data
Learning from Data
Curriculum
4 Sections
16 Lessons
10 Weeks
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Chapter 17: Exploring Four Simple and Effective Algorithms
4
1.1
Guessing the Number: Linear Regression
1.2
Moving to Logistic Regression
1.3
Making Things as Simple as Naïve Bayes
1.4
Learning Lazily with Nearest Neighbors
Chapter 18: Performing Cross-Validation, Selection, and Optimization
4
2.1
Pondering the Problem of Fitting a Model
2.2
Cross-Validating
2.3
Selecting Variables Like a Pro
2.4
Pumping Up Your Hyperparameters
Chapter 19: Increasing Complexity with Linear and Nonlinear Tricks
5
3.1
Using Nonlinear Transformations
3.2
Regularizing Linear Models
3.3
Fighting with Big Data Chunk by Chunk
3.4
Understanding Support Vector Machines
3.5
Playing with Neural Networks
Chapter 20: Understanding the Power of the Many
3
4.1
Starting with a Plain Decision Tree
4.2
Making Machine Learning Accessible
4.3
Boosting Predictions
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