Unit2 Nonlinear Classification, Linear regression, Collaborative Filtering Project 2: Digit recognition (Part 1) プロジェクトの概要 MNISTのデータについて 問題 1. Introduction 2. Linear Regression with Closed Form Solution 3. Support Vector…

What you learned Lec 17: Introduction to Bayesian Statistics frequentist 古典的な統計学。Unit4までやってきた統計。Bayesianに対する言葉。 frequentist vs bayesian bayesian 特徴 prior beliefを具現化したprior distributionをdataでupdateして、po…

Unit3 Methods for estimation What you learned Lec8: Distance measures between distributions Unit2までは、estimatorをsample aveとして直感的に決めてきた 今回は、最適なestimatorを決める手法を学ぶ 今までは、sample aveの期待値がLLNよりパラメー…

Unit1 Introduction to Statistics What you learned Lec1: What is statistics Lec2: Probability Redux Sample average estimatorとして使う probabilistic tools LLN(Laws(weak and strong) of large numbers) a.s. convergence Convergence in probabili…