fineai.com

sidharthshah.github.io

DataMeet Mumbai: Analytics and Land

http://sidharthshah.github.io/meetup/datascience/2015/06/01/data-meet-mumbai.html

DataMeet Mumbai: Analytics and Land. Jun 1, 2015. Yesterday I had good opportunity to attend DataMeet Mumbai. Overall was a good experience. I’ve documented the meeting in a Google Doc, which I am sharing below. Sidharth [at] fafadiatech [dot] com.

sidharthshah.github.io

Part 3: Python Tricks learned this week

http://sidharthshah.github.io/python/2014/11/03/python-tricks.html

Part 3: Python Tricks learned this week. Nov 3, 2014. This week I was researching on creating a simple server that will run on RaspberryPi and display some images and videos. I learned the following. Using ConfigParser as replacement to .ini files. Pythonic interface to Arduino. Using codecs for encoding/decoding e.g. ROT13. Using heapq for priority queue implementation. Heapq can be combined with multiprocessing to do priority based works. Sidharth [at] fafadiatech [dot] com.

sidharthshah.github.io

First Ruby Code: RSS Crawler

http://sidharthshah.github.io/ruby/programming/2015/05/30/first-ruby-code.html

First Ruby Code: RSS Crawler. May 30, 2015. Today I wrote my first actual Ruby code, I did play with it in past. Couple of comments from writing Ruby code. Ruby felt easy to pickup given that I have worked with Python in Past. Ruby’s tooling is good. Also seems like they have a pretty active community for building and maintaining gems. Ruby package’s documentation are pretty good. I could work with simple-rss. I plan on creating a simple Rails application based on ElasticSearch.

sidharthshah.github.io

Part 1: Python Tricks learned this week

http://sidharthshah.github.io/python/2014/10/13/python-tricks.html

Part 1: Python Tricks learned this week. Oct 13, 2014. This week I did some basic analysis on Jobs posting dataset. Along the way I learn few tricks. Use of compiler.ast for Flattening nested lists. Sorting dictionary by value using operator.itemgetter. Using NLTK to generate Ngrams. Using Counters from collections. Using these in combination not only reduce code size, made code more readable. Sidharth [at] fafadiatech [dot] com.

sidharthshah.github.io

Hello World

http://sidharthshah.github.io/update/2014/09/07/hello-world.html

Sep 7, 2014. I am starting the development log to keep track of my learning with respect to programming technology etc. Stay tuned to get more updates. Sidharth [at] fafadiatech [dot] com.

sidharthshah.github.io

Resources

http://sidharthshah.github.io/resources

Al Zimmermann’s Programming Contests. Wikipedia’s List of Algorithms. CodeChef: Data Structures and Algorithms. CodeChef: What are the must known algorithms for online programming contests? StackOverflow: What are the lesser known but useful data structures? Stack Exchange: Code Golf. Hacking a Google Interview. SOME IMPORTANT COMPETITIVE PROGRAMMING RESOURCES. CS 97SI: Introduction to Competitive Programming Contests. CSE 392 - Programming Challenges. Code template for programming contest.

sidharthshah.github.io

Part 4: Python Tricks learned this week

http://sidharthshah.github.io/python/2015/05/28/python-tricks.html

Part 4: Python Tricks learned this week. May 28, 2015. Been a long time since I’ve update the blog. I have been recently working on an Information Retrieval project. Along the way learned a few tricks. Using python’s abc module to create abstract base classes and methods. Using click module for writing better command line scripts. Using lxml’s iterparse method for speeding up parsing of a large XML file. Using os.linesep for writing to file the correct way. For pretty printing onto terminal.

sidharthshah.github.io

Recomm. Engines

http://sidharthshah.github.io/recommendation-engines

Ruby Toolbox: Recommendation Engines. Graph DB and Tools. Quora: Recommendation Engine Community. Quora: How does LinkedIn’s recommendation system work? Quora: What are some good research papers and articles on recommendation systems and engines? Creating a User-Based Recommender in 5 minutes. Neo4j Spatial, Part 1: Building a Recommendation Engine. Neo4j, A Graph Database For Building Recommendation Engines, Gets A Visual Overhaul. Building a real time, solr-powered recommendation engine. SlideShare: Al...

sidharthshah.github.io

Part 2: Python Tricks learned this week

http://sidharthshah.github.io/python/2014/10/30/python-tricks.html

Part 2: Python Tricks learned this week. Oct 30, 2014. While wandering off on Pythonic Route. On Stack Overflow I discovered few things along the way. Motivation for using generators. Yield and Generators explained. Using enums in Python. Sidharth [at] fafadiatech [dot] com.

sidharthshah.github.io

IR

http://sidharthshah.github.io/information-retrieval

Google All Pair Similarity Search. Wukong - Chineese Search Engine in Go. NELL])(http:/ rtw.ml.cmu.edu/rtw/kbbrowser/). A curated list of speech and natural language processing resources. The CMU-Cambridge Statistical Language Modeling Toolkit v2. Stanford: Natural Language Processing. Data Mining and Text Mining. Challenges in Building Large-Scale Information Retrieval Systems. Tutorial: Web Information Retrieval. Solution for the Search Result Relevance Challenge. Algorithms for Duplicate Documents.