IT Professional Curricula Software Development Solution Area Software Development Principles Developing AI and Machine Learning Solutions with Python
Discover how to implement data classification using various techniques, including Bayesian, and learn to apply various search implementations with Python and scikit-learn.
| Objectives |
AI and ML Solutions with Python: Implementing ML Algorithm Using scikit-learn - work with least absolute shrinkage and selection operator
- demonstrate how to apply Bayesian Ridge regression using scikit-learn
- describe data classification using scikit-learn
- implement classifications with decision trees using scikit-learn
- demonstrate how to work with data classification using vector machines in scikit-learn
- demonstrate how to classify documents with Naive Bayes using scikit-learn
- work with Post model validation using the Cross model algorithm
- demonstrate how to work with cross model implementation using Shufflesplit
- implement poor man's grid search and brute force grid search
- create labels and features to classify data into train and test datasets and apply decision tree classifiers
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