course.dataScience
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Introduction
topic 1. Introduction
topic 2. Work with R & Documentation and deployment of your code
Evaluation
topic 3. How to evaluate output?
topic 4. How to perform evaluation?
Feature reduction
topic 5.1 Feature extraction
topic 5.2 Advcanced feature extraction
Visualization and Exploratory
topic 6. Visualization
topic 7. Exploring/managing data
Unsupervised learning
topic 8. Unsupervised learning
Supervised learning
topic 9. Supervised learning (1/6)
topic 10. Supervised learning (2/6)
topic 11. Supervised learning (3/6)
topic 12. Supervised learning (4/6)
topic 13. Supervised learning (5/6)
topic 14. Supervised learning (6/6)
References and supplementaries
Reference Books
Additional Material
Other References
course.dataScience
Introduction
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Introduction
topic 1. Introduction
topic 2. Work with R & Documentation and deployment of your code
Evaluation
topic 3. How to evaluate output?
topic 4. How to perform evaluation?
Feature reduction
topic 5.1 Feature extraction
topic 5.2 Advcanced feature extraction
Visualization and Exploratory
topic 6. Visualization
topic 7. Exploring/managing data
Unsupervised learning
topic 8. Unsupervised learning
Supervised learning
topic 9. Supervised learning (1/6)
topic 10. Supervised learning (2/6)
topic 11. Supervised learning (3/6)
topic 12. Supervised learning (4/6)
topic 13. Supervised learning (5/6)
topic 14. Supervised learning (6/6)
References and supplementaries
Reference Books
Additional Material
Other References
Read the Docs
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