In Search Of The Truth Projected Onto A Finite Dimension

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OLS

04 Least Squares Projection

04 Least Squares Projection

Linear Regression is statistician's garnish on mathematician's least squares projection

Kang Gyeonghun

2020-03-25

훈러닝 채널에 선형대수 강의 있습니다!

Recent Posts

Introduction to Rcpp and RcppArmadillo
Rtools를 윈도우 환경변수 PATH에 추가하는 방법
Variational Inference and Bayesian Gaussian Mixture Model
Forward and Reverse KL divergence
Interpretation of MLE in terms of KL divergence
Note on Kullback-Leibler Divergence

Categories

Intro to Statistical Learning
Linear Algebra
Optimization
Probabilistic Machine Learning
Rcpp
Statistics
Vector, Matrix Derivatives

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ADABOOST Adaptive Basis Model Bayes Rule Bayesian GMM Bayesian Hierarchy Bayesian Networks Bootstrap CART Clustering Conjugacy D-seperation Determinant Diagonalization EM algorithm Ensemble Learning Frequentist Gaussian Mixtures Generalized Additive Models Gibbs Sampling Intro to Statistical Learning Jacobian k-CV K-means Kernel KL divergence Lagrangian Duality Lasso Latent Variable LDA Linear Adjoint Logistic Regression Markov Chain Matrix Derivatives MCMC Metropolis Hastings MSE Multivariate Normal Naive Bayes Classifier OLS PCA Posterior Approximation Rcpp Regression Splines Ridge Self Adjoint Similar Matrices Singular Value Decomposition Stochastic Process SVM vector derivatives

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