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