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Showing posts from July, 2018

How I did customize "rasa-nlu-trainer" as my own tool

Background I wanted to have a tool for human beings to classify intents and extract entities of texts which were obtained from a raw dataset such as's conversation, Maluuba Frames or here. Then, the output (labeled texts) could be consumed by an NLU tool such as Rasa NLU.

rasa-nlu-trainer was a potential one which I didn't need to build an app from scratch. However, I needed to add more of my own features to fulfill my needs. They were:

1. Loading/displaying raw texts stored by a database such as MongoDB
2. Manually labeling intents and entities for the loaded texts
3. Persisting labeled texts into the database

I firstly did look up what rasa-nlu-trainer's technologies were used in order to see how to implement my mentioned features.
At first glancerasa-nlu-trainer was bootstrapped with Create React App. Create React App is a tool to create a React app with no build configuration, as it said. This tool is also recommended by the official React.js tutorial. I ac…

Performance of a Data Structure

Why data structures matter The fact is that programs are all about processing data. Data structures are referred to how data is organized which affects the time of executing a program.
How to measure the performance of a data structure In order to measure "how fast"/efficiency/performance of a data structure, we measure the performance of its operations. There are four basic operations including reading, searching, insertion, and deletion. A pure time consuming is not used for the measuring because it is not reliable depending on the hardware that it is run on. But instead, we use the term time complexity which refers to how many steps an operation takes.
An example of how a single rule can affect efficiency Let's compare two data structures: Array and Set (with N elements).
1. Array - Reading: 1 step (because the computer has the ability to jump to any particular index in the array)
- Searching: N steps (the worst case with linear search)
- Insertion: N + 1 steps (the wo…

My must-have apps for daily work

There is no doubt that cool apps can help us be more productive and enjoyable at work. For the time being, I really love the following apps which are used by me almost every day.
1. A personal Kanban In fact, a personal kanban is the most useful app for me. Why does it matter? It is not just a to-do list, but it keeps me motivated every day because it helps me be able to know what my "big picture" is. I usually set up my plans together with a path to reach them. KanbanFlow is my preferred tool.
2. A terminal Needless to say, a terminal is a must-have app for every developer, especially the ones use macOS/Linux. Due to its importance, I love to decorate and enhance it to be super exciting with various tools such as iTermoh-my-zsh, and thefuck. ;)

3. A documentation "ecosystem" As a developer, I can not remember all things that I have experimented a day. Moreover, a document is really useful for sharing an idea with other people. I use the set of tools for helping…