Machine Learning

Topics:

Classification

Percepton, Decision Trees, Support Vector Machine, Naive Bayes, Logistic Regression, Bagged Forests, k-Nearest Neighbors

Clustering

K-Means, K-Means++, Hierarchical, Lloyds Algorithm, Gonzalez

Document Similarity

Min Hashing, Locality Sensitive Hashing, n-grams, Jaccard Similarity

Gradient Descent

Batch and Stochastic Gradient Descent

PCA

Singular Value Decomposition: Singular values/vectors, Eigen values/vectors, etc

Regression

Linear Regression, Polynomial Regression, Overfitting, Cross Validation

Streaming/Frequency

Misra-Greis, Count-Min Sketch