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fraud-autoencoder-example

Repository with files used for the blog post "Predicting Fraud with Autoencoders and Keras"

german_stopwords

Extended list of German stopwords for use in Web Projects, Search Engines or every thing else.

headlessbrowsers

A list of (almost) all headless web browsers in existence

hrscraper

keras-aquarium

a small collection of models implemented in keras, including matrix factorization(recommendation system), topic modeling, text classification, etc. Runs on tensorflow.

knit-git-markr-guide

Tools that I use for reproducible research

lab-workshops

Materials for workshops on text mining, machine learning, and data visualization

learning-stm

Learning structural topic modeling using the stm R package.

lectures

Oxford Deep NLP 2017 course

lexicon

A data package containing lexicons and dictionaries for text analysis

librarian_page

librarian.netlify.com

librarrry

linear_model

linear_regression

lol_prediction

lolr

lolr.pro

lstmusix

Building a creative machine with this Long Short Term Memory (LSTM) Network. It's trained on stringified MIDI files and reproduces the song ("Für Elise" in this example) with various diversity-factors.

macro_project

masterthetidyverse

metrics

An R package for common supervised machine learning metrics.

ml_slides

mlgraph

updates are coming soon

mlss-2017

Machine Learning Summer School 2017 in Tubingen

neural_topicmodels

nlp---aspect-based-sentiment-analysis-of-customer-reviews-using-hybrid-pattern-matching

Customer reviews on e-commerce websites play a vital role in driving the customer purchasing behavior. Walmart currently follows an overall five-star rating system and it is not reflective of the actual sentiments expressed by the buyers and the verbal descriptive reviews do not distinctively enlighten prospective customers about the specific aspects in products or services. It is essential for Walmart to mine user reviews to extract sentiments by different aspects specific to every product (like quality, durability, warranty service, pricing, reliability etc.) and service (like shipping, packaging, return/ replacement policies etc.). This process can help draw specific insights about the product and service which will help both Walmart and potential customers to take more informed decisions.

nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

onebrmsmodel

Only one brms model

pairwiser

pdf-conversion-into-text

Converts two-column pdfs in whole paragraphs