- Text Analytics: A Primer - Mar 14, 2017.
Marketing scientist Kevin Gray asks Professor Bing Liu to give us a quick snapshot of text analytics in this informative interview.
- Top /r/MachineLearning Posts, February: Oxford Deep NLP Course; Data Visualization for Scikit-learn Results - Mar 6, 2017.
Oxford Deep NLP Course; scikit-plot: Data Visualization for Scikit-learn Results; Machine Learning at Berkeley's ML Crash Course: Neural Networks; Predicting parking difficulty with machine learning; TensorFlow 1.0 Release
- Introduction to Natural Language Processing, Part 1: Lexical Units - Feb 16, 2017.
This series explores core concepts of natural language processing, starting with an introduction to the field and explaining how to identify lexical units as a part of data preprocessing.
- Natural Language Processing Key Terms, Explained - Feb 16, 2017.
This post provides a concise overview of 18 natural language processing terms, intended as an entry point for the beginner looking for some orientation on the topic.
- Deep Learning Research Review: Natural Language Processing - Jan 31, 2017.
This edition of Deep Learning Research Review explains recent research papers in Natural Language Processing (NLP). If you don't have the time to read the top papers yourself, or need an overview of NLP with Deep Learning, this post is for you.
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- Deep Learning Can be Applied to Natural Language Processing - Jan 16, 2017.
This post is a rebuttal to a recent article suggesting that neural networks cannot be applied to natural language given that language is not a produced as a result of continuous function. The post delves into some additional points on deep learning as well.
- Deep Learning Reading Group: Skip-Thought Vectors - Nov 17, 2016.
Skip-thought vectors take inspiration from Word2Vec skip-gram and attempt to extend it to sentences, and are created using an encoder-decoder model. Read on for an overview of the paper.
- Top KDnuggets tweets, Nov 9-15: #Trump, limits of #prediction; #TensorFlow French-to-English machine translation - Nov 16, 2016.
#Trump, limits of #prediction, and lessons for #DataScience of #polls; A #TensorFlow implementation of French-to-English machine translation using @DeepMindAI ByteNet; 18 top women in #DataScience to follow on Twitter; A complete daily plan for studying to become a #MachineLearning #Engineer
- An NLP Approach to Analyzing Twitter, Trump, and Profanity - Nov 3, 2016.
Who swears more? Do Twitter users who mention Donald Trump swear more than those who mention Hillary Clinton? Let’s find out by taking a natural language processing approach (or, NLP for short) to analyzing tweets.
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- Zaireo: Data Scientist - Oct 13, 2016.
Zaireo, working to build happier, healthier relationships, is looking for a Data Scientist with programming experience to help in the collection, categorisation and use of natural language data.
- SlangSD: A Sentiment Dictionary for Slang Words - Sep 14, 2016.
The Slang Sentiment Dictionary (SlangSD) includes over 90,000 slang words together with their sentiment scores, facilitating sentiment analysis in user-generated contents.
- The Human Vector: Incorporate Speaker Embeddings to Make Your Bot More Powerful - Sep 2, 2016.
One of the many ways in which bots can fail is by their (lack of) persona. Learn how speaker embeddings can help with this problem, and can help improve the persona of your bot.
- Exploring Social Media Diversity with Natural Language Processing - Aug 10, 2016.
This post uses natural language processing on Twitter data to determine the diversity of Twitter accounts the author is following. An innovative take on social media analytics.
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- A Survey of Available Corpora for Building Data-driven Dialogue Systems - Jul 12, 2016.
This post is a summary of Serban, et al. "A Survey of Available Corpora for Building Data-Driven Dialogue Systems," which is of increasing relevance given the recent state of conversational AI.
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- Three Impactful Machine Learning Topics at ICML 2016 - Jul 1, 2016.
This post discusses 3 particular tutorial sessions of impact from the recent ICML 2016 conference held in New York. Check out some innovative ideas on Deep Residual Networks, Memory Networks for Language Understanding, and Non-Convex Optimization.
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- U. Chicago Center for Data Science and Public Policy: Postdoc in Natural Language Processing - Jun 29, 2016.
Are you interested in using your natural language processing skills to make a social impact? Want to work with the White House and a team from government, academia, and industry to change how job training programs are created all over the US?
- An Inside Update on Natural Language Processing - Jun 28, 2016.
This article is an interview with computational linguist Jason Baldridge. It's a good read for data scientists, researchers, software developers, and professionals working in media, consumer insights, and market intelligence. It's for anyone who's interested in, or needs to know about, natural language processing (NLP).
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- 5 More Machine Learning Projects You Can No Longer Overlook - Jun 28, 2016.
There are a lot of popular machine learning projects out there, but many more that are not. Which of these are actively developed and worth checking out? Here is an offering of 5 such projects.
- AIG: Senior Manager/Director, Scientist – Natural Language Processing Research - Jun 3, 2016.
AIG is seeking a Senior Manager/Director, Scientist, Natural Language Processing Research, who is a dynamic individual looking to support new transformational projects with a substantial amount of external research participation and internal business partnership.
- Microsoft is Becoming M(ai)crosoft - Apr 25, 2016.
This post is an overview and discussion of Microsoft's increasing investment in, and approach to, artificial intelligence, and how their philosophy differs from their competitors.
- 3 Signs That BI Will Never Be The Same Again - Apr 22, 2016.
Gartner officially deemed 2016 the year of Modern BI and with this new era of BI changes are inevitable. Understand how the traditional BI is reshaping in this data century with Scrollytelling, citizen data scientist and new BI approaches.
- Civis Analytics: Data Scientist, Natural Language Processing - Apr 1, 2016.
Be part of the Research and Development team, responsible for developing the fundamental data science methods, techniques, and best practices that power the mission of our company, performing predictive analytics, algorithm development, experimental design, visualization, and survey research.
- Watson Developer Challenge: build conversational apps using Watson language APIs - Mar 18, 2016.
Watson Developer Challenge is an online hackathon to build conversational apps using Watson new language service APIs for NLP, document conversion, and speech and machine learning algorithms. Coders have till Apr 15 to build software that lets users interact with Watson through a natural conversational interface.
- Interview: Hobson Lane, SHARP Labs on the Beauty of Simplicity in Analytics - May 13, 2015.
We discuss Predictive Analytics projects at Sharp Labs of America, common myths, value of simplicity, tools and technologies, and notorious data quality issues.
- Interview: Haile Owusu, Mashable on Riding the Wave of Viral Content - Apr 29, 2015.
We discuss Mashable’s milestones, data-driven digital publishing, digital media tracking, viral prediction, and Mashable Velocity.
- Text Analytics, Text Mining Courses on Statistics.com - Apr 28, 2015.
Text analytics or text mining is the natural extension and essential part of predictive analytics and Data Science - learn key skills with Statistics.com online courses.
- ADW, free software to measure semantic similarity - Oct 13, 2014.
ADW is a software for measuring semantic similarity of arbitrary pairs of lexical items, from word senses to texts, based on "Align, Disambiguate, and Walk", a WordNet-based state-of-the-art semantic similarity approach. Get it on github.
- Big Data Is Not Big Context - Oct 12, 2014.
Learn about common misconceptions when approaching big data problems, and how the ambiguity of human language requires more sophisticated techniques for more accurate understanding.
- Get Started in Text Analytics - Sep 30, 2014.
Text analytics / text mining is the natural extension of predictive analytics and has wide applications in marketing, business, and many industries. Learn text analytics with Statistics.com online program that starts Feb 6.