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All Programs
Computers
Data Science
Machine Learning
Learning from Smart and Big Data
Learning from Smart and Big Data
Curriculum
6 Sections
24 Lessons
10 Weeks
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Chapter 11: Preprocessing Data
10
1.1
Gathering and Cleaning Data
1.2
Repairing Missing Data
1.2
Quiz for Gathering and Cleaning Data
8 Questions
1.3
Transforming Distributions
1.3
Quiz for Repairing Missing Data
7 Questions
1.4
Creating Your Own Features
1.4
Quiz for Transforming Distributions
6 Questions
1.5
Delimiting Anomalous Data
1.5
Quiz for Creating Your Own Features
6 Questions
1.6
Quiz for Delimiting Anomalous Data
7 Questions
Chapter 12: Leveraging Similarity
8
2.1
Measuring Similarity between Vectors
2.2
Using Distances to Locate Clusters
2.2
Quiz for Measuring Similarity between Vectors
7 Questions
2.3
Tuning the K-Means Algorithm
2.3
Quiz for Using Distances to Locate Clusters
7 Questions
2.4
Finding Similarity by K-Nearest Neighbors
2.4
Quiz for Tuning the K-Means Algorithm
7 Questions
2.5
Quiz for Finding Similarity by K-Nearest Neighbors
6 Questions
Chapter 13: Working with Linear Models the Easy Way
9
3.1
Starting to Combine Features
3.2
Mixing Features of Different Types
3.2
Quiz for Starting to Combine Features
7 Questions
3.3
Switching to Probabilities
3.3
Quiz for Mixing Features of Different Types
6 Questions
3.4
Guessing the Right Features
3.5
Learning One Example at a Time
3.5
Quiz for Guessing the Right Features
5 Questions
3.6
Quiz for Learning One Example at a Time
6 Questions
Chapter 14: Hitting Complexity with Neural Networks
6
4.1
Revising the Perceptron
4.2
Representing the Way of Learning of a Network
4.2
Quiz for Revising the Perceptron
7 Questions
4.3
Introducing Deep Learning
4.3
Quiz for Representing the Way of Learning of a Network
6 Questions
4.4
Quiz for Introducing Deep Learning
6 Questions
Chapter 15: Going a Step Beyond Using Support Vector Machines
6
5.1
Revisiting the Separation Problem
5.2
Explaining the Algorithm
5.2
Quiz for Revisiting the Separation Problem
6 Questions
5.3
Classifying and Estimating with SVM
5.3
Quiz for Explaining the Algorithm
6 Questions
5.4
Quiz for Classifying and Estimating with SVM
7 Questions
Chapter 16: Resorting to Ensembles of Learners
8
6.1
Leveraging Decision Trees
6.2
Working with Almost Random Guesses
6.2
Quiz for Leveraging Decision Trees
7 Questions
6.3
Boosting Smart Predictors
6.3
Quiz for Working with Almost Random Guesses
6 Questions
6.4
Averaging Different Predictors
6.4
Quiz for Boosting Smart Predictors
5 Questions
6.5
Quiz for Averaging Different Predictors
5 Questions
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