Jekyll and Markdown Syntax Cheatsheet
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Study Notes
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Stream Computing emerges when we perform computational tasks at the edge nodes or the incoming stream is too fast and huge to store locally. In this context, we cannot temporarily store the incoming stream elements and process them in memory. Stream Computing is relevant when we have very limited space to store stream elements, or we do not even consider storing them at the first place. Inspecting the performance, accuracy and formally prove them is the main task of analyzing a stream algorithm.
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This note illustrates how to share folders and files between a Windows host and Linux guest through a interconnected virtual network interface. In this setting, where Windows has the Hyper-V platform and the Samba service (including cifs support) installed and Linux OS is deployed in a Hyper-V virtual environment, host OS and guest OS are connect to a same network so that they can communicate each other.
本篇笔记记录如何利用虚拟网卡在Windows操作系统中与Hyper-V平台中的Linux虚拟机共享文件和文件夹。本文的情景为:Linux虚拟机安装在Hyper-V平台中利用虚拟网卡与主机通讯,并且需要读写Windows系统中的文件或文件夹。
NLP tasks and applications.
How words are arranged.
How words form meaning
Feedforward and recurrent models for NLP tasks.
Part Of Speech (POS) tags, approach to tackle the challenge of ambiguity in text. Tag sets, taggers, Hidden Markov Model are summarized.
Text classification is one of the most commonly and widely known NLP tasks. In this note, several text classification tasks, algorithms for different tasks and their evaluation are summarized.
Words, Sentences, Paragraphs, Documents, Corpus are all sparse. they are made up of characters and have uncountable variations. Let’s simplify the question: How can we learn from the meaning of a piece of text based on a given corpus? Language Models are devised to tackle this challenge. In this notes, N-gram Model, its smoothing, application and evaluation are summarized.
Next you can update your site name, avatar and other options using the _config.yml file in the root of your repository (shown below).
Preprocessing is the first step of almost all NLP tasks. What techniques are commonly used? Why is it important? Which preprocessing techniques should we use in a specific task? How it will affect the outcome?
An Introduction to Natural Language Processing, its histories, techniques and applications.