In this project we will try to build and train a skip gram model to obtain vectors for words in the dataset: (word2vec)¶

Table of Contents¶

A simple introduction to python:¶

Python is simple, fast and most importantly easy to learn language. Though I am not an expert at languages a good programming language should not make you worry or think about the implementation over logic.

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Table of Contents¶

Python : Setup and Installation¶

Its a good news for mac book and linux users: In either case python is comes out of the box and you need not install it. But in case of windows please follow the below setup instructions:

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Table of Contents¶

Regular expressions¶

Intro¶

When it comes to text mining you need to understand that a text is nothing but a sequence of characters. The character can be a digits, alphabets, symbols, spaces, new line etc. And in this chapter we are going to learn about regular expressions a very powerfull concept that helps us to play with text. It can be used for finding patterns, searching words or characters, substitution etc.

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Sentiment Analysis:¶

The whole idea of text mining is about gaining insights in textual data. Sentiment anaysis is one of the important applications in the area of text mining. It tries to identify weather the opinoin expressed in a text is positive, negitive or netural towards a given topic.

For example,

1. I am happy about my promotion
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