Index
A
- activation functions, Neurons-Activation Functions
- Adaboost, Boosting
- Adzic, Gojko, Writing the Right Software
- Agile Manifesto, Testing or TDD
- algorithms summary, What Can Machine Learning Accomplish?-What Can Machine Learning Accomplish?, Machine Learning Algorithms Revisited-Machine Learning Algorithms Revisited
- AmazonFresh, Writing the Right Software
- artificial neural networks, History of Neural Nets
B
- back propagation algorithm, Training Algorithms, The Delta Rule
- bagging, Bagging-Bagging, Bagging
- Bain, Alexander, History of Neural Nets
- Bayes' theorem, Inverse Conditional Probability (aka Bayes’ Theorem)
- (see also Naive Bayesian Classification)
- BeautifulSoup, EmailObject
- Beck, Kent, Testing or TDD
- Boolean logic, Boolean Logic
- boosting, Boosting-Boosting
- bootstrap aggregation (see bagging)
- Brown Corpus, Part-of-Speech Tagging with the Brown Corpus-How to Make This Model Better
- (see also part-of-speech tagging with the Brown Corpus)
C
- chain rule, The Chain Rule
- Changing Anything Changes Everything (CACE), SRP
- clustering, Clustering-Conclusion, How to Use This Information to Solve Problems
- consistency in, The Impossibility Theorem
- data gathering, Gathering the Data
- EM algorithm, EM Clustering-Maximization, EM Clustering Our Data-The Results from the EM Jazz Clustering
- example with music categorization, Example: Categorizing Music-The Results from the EM Jazz Clustering
- fitness functions, Fitness of a Cluster
- ground truth testing, Comparing Results to Ground Truth
- and the impossibility theorem, The Impossibility ...
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