Arun Nair's repositories
BanditsBook
Code for my book on Multi-Armed Bandit Algorithms
Bios8366
Advanced Statistical Computing at Vanderbilt University's Department of Biostatistics
boston-airbnb-geo
A Deep Dive into Geospatial Analysis in Python (Tutorial)
deep-learning-tutorial-pydata2016
Deep learning tutorial for PyData London 2016
filterpy
Kalman filtering and optimal estimation library in Python. Kalman filter, Extended Kalman filter, Unscented Kalman filter, g-h, least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
grokking_algorithms
Code for the book Grokking Algorithms (http://manning.com/bhargava)
kaggle-tools
Some tools that I often find myself using in Kaggle challenges.
kaggler-template
Template for data science competitions. Includes makefiles and Python scripts for feature engineering, cross validation, ensemble, etc.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
lightning
Data Visualization Server
linkurious.js
A Javascript toolkit to speed up the development of graph visualization and interaction applications.
machine-learning-for-software-engineers
A complete daily plan for studying to become a machine learning engineer.
maladksad
Jekyll port of Casper, the Medium-like Ghost default’s theme.
ML_for_Hackers
Code accompanying the book "Machine Learning for Hackers"
Neural_Networks-WelchLabs
This python notebook follows neural networks tutorial series by Welch Labs.Link :- http://www.welchlabs.com/blog/2015/1/16/neural-networks-demystified-part-1-data-and-architecture# <Instructor Notebooks Links--->> http://nbviewer.jupyter.org/github/stephencwelch/Neural-Networks-Demysitifed/blob/master/Part%201%20Data%20and%20Architecture.ipynb
newspaper
News, full-text, and article metadata extraction in Python 3
numerical-mooc
A course in numerical methods with Python for engineers and scientists: currently 5 learning modules, with student assignments.
Pandas-Time-Series-Data-Basics
The Pandas library provides simple, but powerful tools to perform any data tasks, especially when it comes to time series data. In this notebook I will be covering 3 basic functionalities for manipulating time series data: Date Ranges, DatetimeIndex & Timestamps and Resampling.
PyCrop
Python implementation of a simple modular 1D crop model.
pygraphml
Small library to parse GraphML file in Python
Shikherverma.github.io
Jekyll CleanBlogEnhanced theme
Sociopedia-Twitter-Knowledge-Engine
Building a search engine to discovery web services specified using a natural language query that infers relationships using an ontology of Twitter data. Technologies used are NLTK, Python, Whoosh, Django and CMU Ark Tweet Parser. The fast information sharing on Twitter from millions of users all over the world leads to almost real-time reporting of events. It is extremely important for business and administrative decision makers to learn events popularity as quickly as possible, as it can buy extra precious time for them to make informed decisions. Therefore, we introduce the problem of predicting future popularity trend of events on microblogging platforms. Traditionally, trend prediction has been performed by using time series analysis of past popularity to forecast the future popularity changes.
time-series-classification-and-clustering
Time series classification and clustering code written in Python. Mostly based on the work of Dr. Eamonn Keogh at University of California Riverside
visualize_ML
Python package to visualize some processes involved in Machine learning.
XGBoost-Course-Docker
XGBooster training
zeppelin-notebooks
Gallery of Apache Zeppelin notebooks
zipline
Zipline, a Pythonic Algorithmic Trading Library