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data-science-reference-library's Introduction

cheatsheets

A central repo on some of the tools and technologies picked up over time

Machine Learning
├── Supervised Learning
│   ├── Regression
│   │   ├── Linear Regression
│   │   ├── Polynomial Regression
│   │   ├── Decision Tree Regression
│   │   ├── Random Forest Regression
│   │   └── Other regression algorithms
│   └── Classification
│       ├── Logistic Regression
│       ├── Decision Tree Classification
│       ├── Random Forest Classification
│       ├── Support Vector Machines (SVM)
│       ├── Naive Bayes Classification
│       ├── K-Nearest Neighbors (KNN)
│       └── Other classification algorithms
└── Unsupervised Learning
    ├── Clustering
    │   ├── K-Means Clustering
    │   ├── Hierarchical Clustering
    │   ├── DBSCAN
    │   └── Other clustering algorithms
    └── Dimensionality Reduction
        ├── Principal Component Analysis (PCA)
        ├── Singular Value Decomposition (SVD)
        ├── t-Distributed Stochastic Neighbor Embedding (t-SNE)
        └── Other dimensionality reduction techniques

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