1. Measurable Space and Integration

real analysis Real and Complex Analysis

The [Real Analysis] series of posts is my memo on the lecture Real Analysis (Spring, 2021) by Prof. Insuk Seo. The lecture follows the table of contents of Real and Complex Analysis (3rd ed.) by Rudin, with minor changes in order.

1. Brief Introduction to Nonparametric function estimation

nonparametric spline kernel

The [Nonparametric] series of posts is my memo on the lecture Nonparametric Function Estimation (Spring, 2021) by Prof. Byeong U. Park. The lecture is mainly focused on kernel smoothing, while also briefly covers other nonparametric methods such as MARS.

1. Overview of Supervised Learning

statistical learning The Elements of Statistical Learning

The [Statistical Learning] series of posts are my summary of The Elements of Statistical Learning (ESL) and a memo on the lecture Advanced Data Mining (Spring, 2021) by Prof. Yongdai Kim. Main goal of the lecture is to interpret classical machine learning models in terms of statistics and decision theoretic framework.

Understanding ELMo

machine learning natural language processing

Word2Vec and FastText paved the way to quality word embedding by utilizing context information, either word-level or character-level. ELMo (embeddings from language model) improved upon those with not only single context, but with both character and word-level contexts by dedicated architecture for the tasks.