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capturetweet

Python project to capture tweets

churn-analysis---telecom

Prediction of propensity to churn from the usage behavior using logistic regression.

code_snippets

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

credit_card_fraud

This repository includes the code used in my corresponding Medium post.

customer-churn-in-telecommunications

A project on customer churn in the telecommnications sectoer. The aim of this project is to identify customers that are likely to churn.

customer-chuurn-in-telecommunicatiomns

data-scientist-resume-latex

A LaTeX resume template, tailored for the recent graduate who aspires to be a Data Scientist.

data-wrangling

The purpose of this project is to gather data using Tweepy python library and with gathered data and given archived dataset, wrangle WeRAteDogs Twitter data to create analyses and visualizations.

datascience-ai-machinelearning-resources

Alex Castrounis' curated set of resources for artificial intelligence (AI), machine learning, data science, internet of things (IoT), and more.

datasciencecoursera

datasharing

The Leek group guide to data sharing

dtree

A simple pure-Python decision tree construction algorithm

go

The Open Source Data Science Masters

hillary-clinton-emails

Code to transform Hillary's emails from raw PDF documents to a SQLite database

linear_regression_live

This is the code for the "How to Do Linear Regression the Right Way" live session by Siraj Raval on Youtube

marketing-data-science

Analytics and data science business case studies to identify opportunities and inform decisions about products and features. Topics include Markov chains, A/B testing, customer segmentation, and machine learning models (logistic regression, support vector machines, and quadratic discriminant analysis).

new

python_wrangle-and-analyze-data

Real-world data rarely comes clean. Using Python and its libraries, I will gather data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. This is called data wrangling. I had documented my wrangling efforts in a Jupyter Notebook, plus showcased them through analyses and visualizations using Python (and its libraries) and/or SQL. The dataset that i wrangled (and analyzed and visualized) is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent." WeRateDogs has over 4 million followers and has received international media coverage. WeRateDogs downloaded their Twitter archive and sent it to Udacity via email exclusively to use in this project. This archive contains basic tweet data (tweet ID, timestamp, text, etc.) for all 5000+ of their tweets as they stood on August 1, 2017. More on this soon.

sample_app

social-media-listening

Python code for listening to Streaming APIs

sociallistening

Read APIs from different social media sight and find words that are trending.

software

test

test-repo

demo

time

Regression and Time Series for Actuaries

time_series_forecasting

Time_series_forecasting in R using ARIMA,Auto ARIMA ,Arimax and Holt Winters

titanic

An R data package containing Titanic datasets

tweepy

Twitter for Python!

twit-list

LISTENING, SOCIALLY