Recommender system designThis post mainly focus on the high-level architecture and design of a recommender system in the context of a news APP. It tends to focus…Oct 26, 2020Oct 26, 2020
From Static Embedding to Contextualized EmbeddingThis post summarizes a bunch of recent representative and influential results in the area of word embedding (Even though the idea is…Sep 8, 2020Sep 8, 2020
Demystify TransformerTransformer is a model architecture that based solely on attention mechanisms without using recurrence and convolutions. Without the…Feb 5, 2020Feb 5, 2020
Summary of algorithms in Stanford Machine Learning (CS229) Part IIIIn this post, we will continue the summarization of machine learning algorithms in CS229. This post focus mainly on reinforcement learning…Jan 1, 2020Jan 1, 2020
Summary of algorithms in Stanford Machine Learning (CS229) Part IIIn this post, we will continue the summarization of machine learning algorithms in CS229. This post focus mainly on unsupervised learning…Dec 26, 2019Dec 26, 2019
Demystify TF-IDF in Indexing and RankingTF-IDF (term frequency-inverse document frequency) can be thought of as a numerical metric that reflects how important a word is in a…Dec 14, 20193Dec 14, 20193
Summary of algorithms in Stanford Machine Learning (CS229) Part IIn this post, I would like to summarize all thFe algorithms taught in CS229. I will split the material into three parts: supervised…Dec 8, 2019Dec 8, 2019
