Introduction to text mining with Julia

April 14, 2014

We are Data Science enthusiasts, and excited about this new language called Julia ( julialang.org), and would like to share some of our experience and findings:

1. Introduction to Julia

• Why Julia language

• History of Julia

• Benchmarks on performance of Julia and information on current contributions to Julia

• Strings, Arrays, Dictionaries, DataFrames

• Types, Constructors, Multiple Dispatch

2. Introduction to Text Mining with Julia - A Mathematical Approach

In this hands-on session we will learn and apply the mathematical concepts to build various models for the information retrieval task of text mining. We would deal with LinAlg concepts of vectors and spaces. All the below mentioned topics would be a guided walk-through of the math, simple enough for anyone with elementary math knowledge, and have some fun with it to build models for text mining.

• What is Text Mining?

• Preparation for Text Mining

• Quantization of Text

• Query Matching

• Performance Modeling

• Vector Space Model

• Latent Semantic Index Model

• K-Means Model

• Performance Analysis

• Discussion

Note :

1. It is required for the attendees to have a laptop with Julia installed. Please refer to http://julialang.org/downloads/ for instructions.

2. Please also clone the following repository : https://github.com/abhi123link/JuliaTutorial.jl/

3. The packages which are required are in the Require file. You can install them through, Pkg.add("Clustering") etc.


Event Details

Time & Date

Start: April 19, 2014 at 11:00 AM IST
End: April 19, 2014 at 1:00 PM IST


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