abhermida

abhermida's Stars

• h5bp/html5-boilerplate

  A professional front-end template for building fast, robust, and adaptable web apps or sites.

  Language:JavaScript56.5k2.5k1.3k12.2k

• hashicorp/vault

  A tool for secrets management, encryption as a service, and privileged access management

  Language:Go31.1k8156.2k4.2k

• claudiodangelis/qrcp

  :zap: Transfer files over wifi from your computer to your mobile device by scanning a QR code without leaving the terminal.

  Language:Go10k110164530

• zihangdai/xlnet

  XLNet: Generalized Autoregressive Pretraining for Language Understanding

  Language:Python6.2k1712631.2k

• rstudio/cheatsheets

  Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/.

  Language:TeX5.8k23201.8k

• licensee/licensee

  A Ruby Gem to detect under what license a project is distributed.

  Language:Ruby78756263266

• pemistahl/lingua

  The most accurate natural language detection library for Java and the JVM, suitable for long and short text alike

  Language:Kotlin7061112963

• v4d1/SpoofThatMail

  Bash script to check if a domain or list of domains can be spoofed based in DMARC records

  Language:Shell3149155

• mitchelljy/Trending-YouTube-Scraper

  Python script that scrapes the currently trending YouTube videos in a variety of countries

  Language:Python3061311158

• crabcamp/lexrank

  LexRank algorithm for text summarization

  Language:Python2294541

• nicolaspascual/mercadona-scrapper

  Scrapper for the web page of mercadona. It downloads all current products into a csv file

  Language:Python442114

• victor7246/jointtsmodel

  Library of Joint Topic-Sentiment Models

  Language:Python332410

• informatiCup/informatiCup2020

  Pandemie!

  Language:JavaScript208265

• CodiumTeam/tdd-training-java

  Katas for the Codium TDD training in Java

  Language:Java123013

• Top-Ranger/ClassifyHub

  Classification of GitHub repositories - developed for the InformatiCup 2017

  Language:Python9403

• reenathomas18/Amazon-Review-Comments---Latent-Dirichlet-allocation

  Help a leading mobile brand understand the voice of the customer by analyzing the reviews of their product on Amazon and the topics that customers are talking about. You will perform topic modeling on specific parts of speech. You’ll finally interpret the emerging topics. Problem Statement: A popular mobile phone brand, Lenovo has launched their budget smartphone in the Indian market. The client wants to understand the VOC (voice of the customer) on the product. This will be useful to not just evaluate the current product, but to also get some direction for developing the product pipeline. The client is particularly interested in the different aspects that customers care about. Product reviews by customers on a leading e-commerce site should provide a good view4 Domain: Amazon reviews for a leading phone brand Analysis to be done: POS tagging, topic modeling using LDA, and topic interpretation

  Language:Jupyter Notebook83