Machine Learning with Scikit-Learn

  1. Core Scikit-Learn Concepts and API
    1. The Estimator API
      1. Overview of the Estimator Pattern
        1. The `fit()` Method
          1. Purpose and Usage
            1. Input Data Requirements
              1. Parameter Learning
              2. The `predict()` Method
                1. Purpose and Usage
                  1. Output Interpretation
                    1. Prediction Types
                    2. The `predict_proba()` Method
                      1. Probability Predictions
                        1. Use Cases
                        2. The `transform()` Method
                          1. Purpose and Usage
                            1. Use with Transformers
                              1. Data Transformation
                              2. The `fit_transform()` Method
                                1. Combined Fitting and Transformation
                                  1. Efficiency Considerations
                                  2. The `score()` Method
                                    1. Purpose and Usage
                                      1. Default Scoring Metrics
                                      2. The `get_params()` and `set_params()` Methods
                                        1. Parameter Inspection
                                          1. Parameter Modification
                                        2. Objects in Scikit-Learn
                                          1. Estimators
                                            1. Definition and Role
                                              1. Types of Estimators
                                              2. Predictors
                                                1. Definition and Role
                                                  1. Supervised Learning Estimators
                                                  2. Transformers
                                                    1. Definition and Role
                                                      1. Data Preprocessing Role
                                                      2. Meta-Estimators
                                                        1. Definition and Examples
                                                          1. Ensemble Methods
                                                            1. Model Selection Tools
                                                          2. Datasets in Scikit-Learn
                                                            1. Understanding Data Structure
                                                              1. Features (X)
                                                                1. Target (y)
                                                                  1. Data Shapes and Types
                                                                    1. Sparse vs Dense Matrices
                                                                    2. Loading Sample Datasets
                                                                      1. Accessing Built-in Datasets
                                                                        1. Dataset Structure and Attributes
                                                                        2. Toy Datasets
                                                                          1. Iris Dataset
                                                                            1. Digits Dataset
                                                                              1. Wine Dataset
                                                                                1. Breast Cancer Dataset
                                                                                  1. Boston Housing Dataset
                                                                                  2. Real-World Datasets
                                                                                    1. California Housing Dataset
                                                                                      1. Olivetti Faces Dataset
                                                                                        1. 20 Newsgroups Dataset
                                                                                          1. Fetching External Datasets
                                                                                          2. Generating Synthetic Data
                                                                                            1. `make_classification`
                                                                                              1. `make_regression`
                                                                                                1. `make_blobs`
                                                                                                  1. `make_moons`
                                                                                                    1. `make_circles`
                                                                                                      1. `make_multilabel_classification`
                                                                                                      2. Loading Data from External Sources
                                                                                                        1. CSV Files
                                                                                                          1. Excel Files
                                                                                                            1. JSON Files
                                                                                                              1. SQL Databases
                                                                                                                1. Web APIs

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                                                                                                            1. Introduction to Scikit-Learn

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                                                                                                            3. Machine Learning Fundamentals