Notes - intro. to machine learning
- Introduction
- Supervised Learning
- Classification and Regression [Notebook] [Shqip]
- Generalization, Overfitting and Underfitting [Notebook] [Shqip]
- Supervised Machine Learning Algorithms [Notebook] [Shqip]
- k-Nearest Neighbor [Notebook] [Shqip]
- Linear models [Notebook] [Shqip]
- Naive Bayes Classifiers [Notebook] [Shqip]
- Decision trees [Notebook] [Shqip] [Practice]
- Ensembles of Decision Trees [Notebook] [Shqip][Practice]
- Kernelized Support Vector Machines [Notebook] [Shqip]
- Neural Networks (Deep Learning) [Notebook] [Shqip]
- Uncertainty estimates from classifiers [Notebook] [Shqip]
- Unsupervised Learning and Preprocessing
- Representing Data and Engineering Features
- Categorical Variables
- Binning, Discretization, Linear Models and Trees
- Interactions and Polynomials
- Univariate Non-linear transformations
- Automatic Feature Selection
- Utilizing Expert Knowledge
- Model evaluation and improvement
- Cross-validation
- Grid Search
- Evaluation Metrics and scoring
- Algorithm Chains and Pipelines
- Parameter Selection with Preprocessing
- Working with Text Data
- Types of data represented as strings
- Topic Modeling and Document Clustering