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# Introduction

This blog will give a simple explanation of BERT and its variants’(Mainly focus on variants) main idea and how these models improve base on its training process.

# Introduction

Hello, nice to meet you! This is my summary of my recent learning and it will continue updating for some time since I’m still learning. I will summarize some method of Intention Recognization that I learned from paper recently. I will just show the main idea about a specific without too many details. I will list the paper that corresponding to the topic that I’m showing below. If you are interested in some topics, you can find the original paper and get more details. Always, if you want to talk with me, please contact me at haroldliuj@gmail.com. Let’s get Started! Have a nice trip!

# Introduction

This is my reading notes for Yin J, Wang J’s A Dirichlet Multinomial Mixture model-based approach for short text clustering. I explained the main idea of this paper and summarized the paper with both the author’s explanations and my understanding. If you want to talk about this paper with me, please contact me at haroldliuj@gmail.com. Have a good trip!

# Introduction

This is my reading notes of Vaswani A, Shazeer N, Parmar N, et al’s Attention Is All You Need. I just briefly summarized the logistic structure of the paper and list the main idea of the paper. If you need more details of the paper, please read the passage by yourself. If you have any questions want to discuss with me, feel free to contact at haroldliuj@gmail.com. Have a nice trip!

## Introduction

This is my reading notes for Gao et al’s Neural Approaches to Conversational AI. I just marked something I think is important and made the structure more logistic clear. Since I just read the paper once, there must be something that I wrongly understood. Feel free to contact me at haroldliuj@gmail if you find something wrong. Have a nice trip!

## Introduction

This is my lecture notes for UC Berkeley course Data Science for Research Psychology instructed by Professor Charles Frye. This post contains some basic data science and statistic knowledge. Most of the content showed following is from this course’s lecture slides with some of my understanding. You can check the original slides at here. If there are any copyright issues please contact me: haroldliuj@gmail.com.

## Introduction

This is my lecture notes for UC Berkeley course Data Science for Research Psychology instructed by Professor Charles Frye. This post contains some basic data science and statistic knowledge. Most of the content showed following is from this course’s lecture slides with some of my understanding. You can check the original slides at here. If there are any copyright issues please contact me: haroldliuj@gmail.com.

# Stanford CS224n Learning Notes 1: Word Vectors

This blog is just my learning notes of Stanford CS224n so I used many expressions and graphs from slides and lecture readings. If there are copyright problems, please contact me.

• This blog may contain Xiao(Harold) Liu’s learning notes about what he recent learned and some photos that he recently took.
• Have a nice trip!!
• $Name(Xiao) = Harold$
• 文章可能并不只限于同一语种