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Natural Language Processing

Natural language processing (NLP) is the study of how computers and humans interact.
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Practices github.com

Natural Language Processing best practices & examples

The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in NLP algorithms, neural architectures, and distributed machine learning systems. The content is based on our past and potential future engagements with customers as well as collaboration with partners, researchers, and the open source community.

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Google github.com

Using Google's speech recognition to beat Google's ReCaptcha

A little ingenuity paired with changes to ReCaptcha’s audio challenge allowed this hacker to create a Python ‘robot’ that defeats the ‘not a robot’ test with 90% accuracy. The approach is brilliant: Navigate to Google’s ReCaptcha Demo site Navigate to audio challenge for ReCaptcha Download audio challenge Submit audio challenge to Speech To Text Parse response and type answer Press submit and check if successful The code is small enough to grok in 5-10 minutes. Love it!

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TensorFlow cvcompiler.com

An NLP tool for improving dev resumes

CV Compiler is an online resume analysis tool designed exclusively for software engineers. The review technology scans for keywords from the world of programming and how they are used in the resume, relative to the best practices in the industry. CV Compiler was built using Python with libraries NLTK and spaCy for tokenization, lemmatization, and POS-tagging. The internal analysis engine for large datasets (resumes, job descriptions) was built upon a Seq2Seq model in TensorFlow.

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