Today was the last day of the main conference of the Annual Meeting of Association for Computational Linguistics (ACL). It is my first ACL. Thanks to my professor Dr. Thamar Solorio for supporting me to attend this amazing event. I’ve attended some amazing talks, had a chance to visit some posters with cool ideas, talked to some great people. Just came back to hotel and thought lets write about some memories?
Because of my primary interests in semantics, sentiments and information extraction I’ve attended these sessions. Here are the talks I found so exciting and marked to read the papers soon and possibly use in my work. Continue reading
This post demonstrates 2 different ways in Erlang to fetch ranking information of books from Amazon. The input of this program is a file named ISBN.txt and as the output books, information (ISBN, Book title and Rank) will be displayed sorted by the rank. We will do this job in both sequential way and concurrent way. Continue reading
Generating Fibonacci sequence is definitely not a complex problem to talk about. We all did it in our early stage of programming. So I am not going to explain what it is. Let’s talk about the ways we can generate it in our familiar languages. Continue reading
Recently I have explored some really cool stuff of programming. I wasn’t much familiar with functional programming as I am used to imperative programming. I guess it’s okay, to be honest, and say that I have wasted my time writing a lot of noisy and garbage like code from the beginning of my introduction to programming. Continue reading
I was used to solving problems in UVA online judge around 2009. I uploaded the solutions in my old website sudiptakar.freetzi.com. That site was discontinued from 2012 and I’ve lost most of the codes. I didn’t move the codes on this site. After a long time, I could retrieve some of the codes (around 105 problems). They are available on Github.
You are welcome to watch the code for help. But try to solve the problem by yourself first. It will help your learning.
I was trying to extract n-gram features from a large dataset and got a memory error. I was using TfIdfVectorizer of scikit-learn. And the error was from the large sparse matrix. I was not surprised as I was not sure if my 32GB ram is enough for around 1 million documents. However, I solved the error by the following steps.