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courses

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

data-analysis-of-titanic-using-python

data-mining-on-social-media

Python scripts to extract tweets and facebook posts from public users.

datasciencecoursera

Coursera data science projects

datasharing

The Leek group guide to data sharing

edx-dl

A simple tool to download video lectures from edx.org (and other openedx sites)

machine-learning-with-python

Python code for common Machine Learning Algorithms

mumbai_city_analysis

An analysis of the neighborhoods of Mumbai, based on property price, living expense, and venues

news-please

news-please - an integrated web crawler and information extractor for news that just works.

nlp-in-practice

Full working examples in Python with accompanying dataset for Text Mining & NLP. Includes: Gensim Word2Vec, phrase embeddings, keyword extraction with TFIDF, word count with pyspark, simple text preprocessing, accessing pre-trained embeddings and more.

nlp_mini_course

Credit: Dr. Brownlee at machinelearningmastery.com

notebooks

Repo for small projects that fit inside a Jupyter Notebook. Inside: word2vec news analysis and regression, tutorial on working with survey data, and more.

philippine-bills

prediction-of-stock-market-with-sentiment-analysis

programmingassignment2

Repository for Programming Assignment 2 for R Programming on Coursera

pythonprojects

Python Scripts for Machine Learning Projects

scrape-news-articles

scraping news articles from Quartz

sentiment-analysis

Implementing twitter sentiment analysis using CNN and LSTMs

sentiment-analysis-of-twitter-data-by-lexicon-approach

This project uses Lexicon-based approach for sentimental analysis of 1000 recent tweets of 4 countries. A sentiment score for each tweet is computed to ascertain the overall nature of the tweet.

stock-market-prediction-using-natural-language-processing

We used Machine learning techniques to evaluate past data pertaining to the stock market and world affairs of the corresponding time period, in order to make predictions in stock trends. We built a model that will be able to buy and sell stock based on profitable prediction, without any human interactions. The model uses Natural Language Processing (NLP) to make smart “decisions” based on current affairs, article, etc. With NLP and the basic rule of probability, our goal is to increases the accuracy of the stock predictions.

stocksentimenttrading

Algorithmic Trading using Sentiment Analysis on News Articles

survivor-alliance-analysis

scraping the Survivor Wiki for voting data; computational analysis of alliances

tia

Toolkit for integration and analysis

tidy-text-mining

Manuscript of the book "Tidy Text Mining with R" by Julia Silge and David Robinson

twitter-past-crawler

A crawler that can accumulate past tweets without the twitter API

whatsapp-analytics

performing sentiment analysis on the whatsapp chats.