Clustering, Errors, & Validation
Data Science
| Beginner
- 10 videos | 33m 17s
- Includes Assessment
- Earns a Badge
Machine learning is a particular area of data science that uses techniques to create models from data without being explicitly programmed. Examine clustering, errors, and validation in machine learning.
WHAT YOU WILL LEARN
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describe K-means clustering
define cluster validation
define principal component analysis
describe machine learning errors
describe underfitting -
describe overfitting
apply k-folds cross validation
describe fall-forward and back-propagation in neural networks
describe SVMs and their use
choose the appropriate machine learning method for the given example problems
IN THIS COURSE
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4m 42s
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4m 26s
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3. Using Principal Component Analysis3m 37s
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4. Introduction to Errors4m 4s
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5. Defining Underfitting3m 25s
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6. Defining Overfitting2m 5s
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7. Using K-folds Cross Validation3m 8s
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8. Using Neural Networks3m 29s
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9. Support Vector Machines (SVM)2m 29s
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10. Exercise: Choose a Machine Learning Method1m 51s
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