# Introduction to BLEU in Python

BLEU is a metric to quantify effectiveness of an Machine Translation (MT). It stands for BiLingual Evaluation Understudy $^{[1]}$. In general it solves the problem of different human translation references by different annotators when comparing to machine generated translation. Let’s start from using BLEU in NLTK translation package $^{[2]}$

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# Productivity Tools

This is my personal choice for productivity tools, you may find these tools usefull but you may also find differently. I use ubuntu desktop and android phone, so my personal choices will based on these platforms.

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# Basic Architecture of Neural Network

graph LR subgraph input layer X1[x1] X2[x2] X3[x3] end subgraph hidden layer H1((h1)) H2((h2)) H3((h3)) end subgraph output layer YHAT((yhat)) end X1 --> H1 X1 --> H2 X1 --> H3 X2 --> H1 X2 --> H2 X2 --> H3 X3 --> H1 X3 --> H2 X3 --> H3 H1 --> YHAT((yhat)) H2 --> YHAT H3 --> YHAT

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# Deep Learning - Week 2.1 Lecture Notes

Short introduction to vector operation in python numpy in logistic regression.

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# Deep Learning - Week 2 Lecture Notes

This is my notes for Deep Learning Course in Coursera. I jumped straight to week 2 because week 1 is about introduction that I’ve known. Week 2 in summary is structured as: starting from binary classification with logistic regression, loss function and cost function, computational graph.

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# TLDL Radical Candor Ep5 - Career Conversation

This is a too long didn’t listen (TLDL) version of radical candor ep.5 summary. As a reminder for myself in the future and a person who prefer reading than listening because I quickly forgot. NB: when I use “people” here it usually means software engineers.

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# Overcome Negative Thoughts and Build Optimism

A general advice on focusing on positive thoughts and less on negative thoughts. I found this will very helpful for me for now and in the future to fight for my thoughts and focus on what’s important. Hopefully this could also be inspiration for anyone else. Special thanks for Talk at Google and Happify to share.

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# How to Do Conjoint Analysis in python

This post shows how to do conjoint analysis using python. Conjoint analysis is a method to find the most prefered settings of a product [11].

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# Summary of Statistics Terms

In this post, I just want to summarize statistics terms, that might be used when analyzing data or reading papers.

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# Virtebi Algorithm and Hidden Markov Model - Part 2

I’ve implemented virtebi algorithm and explain the advantage from naive approach at last post. Now it’s time to look at another use case example: the Part of Speech Tagging!

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# Virtebi Algorithm and Markov Chain - Part 1

Introduction to Virtebi Algorithm, Virtebi Path, Markov Chain, Hidden Markov Model.

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# How to Use One Way ANOVA in Python

One way ANOVA (Analysis of Variance) is a technique for hypothesis testing. It is used to test whether the means of different group is really different.

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# A Simple Bloom Filter

It is a probabilistic data structure, that is commonly used to ask question “whether an element is in it or not?”. From my description, it does seems like a job that Set can do, sooo…