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atom

The hackable text editor :atom:

country-codes

Comprehensive country code information, including ISO 3166 codes, ITU dialing codes, ISO 4217 currency codes, and many others

crime_classification

Crime classification using Neural nets, count featurizer

fundamentals---data-analysis-in-r

R- data analysis

incremental_pca

iso-3166-countries-with-regional-codes

ISO 3166-1 country lists merged with their UN Geoscheme regional codes in ready-to-use JSON, XML, CSV data sets

list-of-us-states

List of US States in various Rails friendly formats

ml---nlp-on-patents-data

Used 9 billion data files for analysis of patent grant prediction using regex, nltk, sci-kit learn, pandas libraries

movie_sentiment_analysis

Sentiment analysis of review text using POS tagging and NLTK library

product_recommendation_santander

In this dataset, you are provided with 1.5 years of customers behavior data from Santander bank to predict what new products customers will purchase. The data starts at 2015-01-28 and has monthly records of products a customer has, such as "credit card", "savings account", etc. You will predict what additional products a customer will get in the last month, 2016-06-28, in addition to what they already have at 2016-05-28. These products are the columns named: ind_(xyz)_ult1, which are the columns #25 - #48 in the training data. You will predict what a customer will buy in addition to what they already had at 2016-05-28.

spam_ham_neuralnets

Used tf-idf , POS tagging, CountVectoriser and Neural nets

uber-ds-challenge

Uber provided Data Science take home

vehicle_reservations

Analysis and recommendations on vehicle reservations