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365psd

A python script to download free psd files from 365psd

algorithms

Algorithms that I m learning from Bob Sedgewick's class

django-rango

Tango with Django - Rango app

emailauthorprediction

For the task of prediction of author from emails, we used Unigram language model. We started out on the problem by finding out the features that would help model the solution. The features that looked important were: • N-grams of the email • Frequency of each N-gram • Out of Vocabulary words (Spelling mistakes) The combination of first two features describes how the particular author chooses his dictionary set for writing text. Therefore, this feature can be termed as the signature of the author as all writers tend to choose only words from some defined subset of the Vocabulary. Also, the out of vocabulary words, generally the spelling mistakes done by the author, depict the style of the writing text, and therefore, comes to be an important aspect of the solution. The solution, thus, comes to be finding the total probability of each Ngram to be written by the particular author in the email.

graphcomponents-mapreduce

ideas

invertedindex

Inverted index based search engine

k-means

K-means clustering

latentsemanticindexing

Search engine that indexed full text using Latent Semantic Indexing

minhash

Estimating how similar are two sets using MinHash (Jaccard similarity coefficient)

pagerank

Mini web search engine using PageRank

print-envelopes

Printing envelopes

python-trees

Python tree implementation

qa-system

Question Answering system

smartass

wordsensedisambiguation

Word Sense Disambiguation

youtube-source-code