- What is Text Classification? - Jul 28, 2022.
We will define text classification, how it works, some of its most known algorithms, and provide data sets that might help start your text classification journey.
- N-gram Language Modeling in Natural Language Processing - Jul 6, 2022.
N-gram is a sequence of n words in the modeling of NLP. How can this technique be useful in language modeling?
- Market Data and News: A Time Series Analysis - Jun 24, 2022.
In this article we introduce a few tools and techniques for studying relationships between the stock market and the news. We explore time series processing, anomaly detection, and an event-based view of the news. We also generate intuitive charts to demonstrate some of these concepts, and share the code behind all of this in a notebook.
- A Gentle Introduction to Natural Language Processing - Jun 17, 2022.
This gentle introduction to NLP covers the basics, and will help you move along to more advanced topics ASAP.
- NLP, NLU, and NLG: What’s The Difference? A Comprehensive Guide - Jun 10, 2022.
This article aims to quickly cover the similarities and differences between NLP, NLU, and NLG and talk about what the future for NLP holds.
- Natural Language Processing Key Terms, Explained - May 16, 2022.
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.
- oBERT: Compound Sparsification Delivers Faster Accurate Models for NLP - May 13, 2022.
Discover "compound sparsification" and how to apply it to BERT models for 10x compression and GPU-level latency on commodity CPUs.
- Can We Query a Table with T5? - May 12, 2022.
Learn how to tune a large language model.
- How Fast Can BERT Go With Sparsity? - Apr 27, 2022.
How much impact does sparsity have on model performance?
- Answering Questions with HuggingFace Pipelines and Streamlit - Apr 14, 2022.
See how easy it can be to build a simple web app for question answering from text using Streamlit and HuggingFace pipelines.
- How to Start Using Natural Language Processing With PyTorch - Apr 13, 2022.
In this guide, we will address some of the obvious questions that may arise when starting to dive into natural language processing, but we will also engage with deeper questions and give you the right steps to get started working on your own NLP programs.
- The Range of NLP Applications in the Real World: A Different Solution To Each Problem - Mar 25, 2022.
Most companies look at it like it’s one big technology, and assume the vendors’ offerings might differ in product quality and price but ultimately be largely the same. Truth is, NLP is not one thing; it’s not one tool, but rather a toolbox.
- Classifying Long Text Documents Using BERT - Feb 3, 2022.
Transformer based language models such as BERT are really good at understanding the semantic context because they were designed specifically for that purpose. BERT outperforms all NLP baselines, but as we say in the scientific community, “no free lunch”. How can we use BERT to classify long text documents?
- Fine-Tuning BERT for Tweets Classification with HuggingFace - Jan 28, 2022.
In this blog, we used the Hugging Face library to fine-tune BERT on the classification task. We classified tweets related to COVID.
- Explain NLP Models with LIME - Jan 21, 2022.
It is important to know how LIME reaches to its final outputs for explaining a prediction done for text data. In this article, I have shared that concept by enlightening the components of LIME.
- A Comprehensive Guide to Natural Language Generation - Jan 7, 2020.
Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.
- Neural Code Search: How Facebook Uses Neural Networks to Help Developers Search for Code Snippets - Jul 24, 2019.
Developers are always searching for answers to questions about their code. But how do they ask the right questions? Facebook is creating new NLP neural networks to help search code repositories that may advance information retrieval algorithms.
- Natural Language Interface to DataTable - Jun 21, 2019.
You have to write SQL queries to query data from a relational database. Sometimes, you even have to write complex queries to do that. Won't it be amazing if you could use a chatbot to retrieve data from a database using simple English? That's what this tutorial is all about.
- Your Guide to Natural Language Processing (NLP) - May 23, 2019.
This extensive post covers NLP use cases, basic examples, Tokenization, Stop Words Removal, Stemming, Lemmatization, Topic Modeling, the future of NLP, and more.
- 50+ Useful Machine Learning & Prediction APIs, 2018 Edition - May 1, 2018.
Extensive list of 50+ APIs in Face and Image Recognition ,Text Analysis, NLP, Sentiment Analysis, Language Translation, Machine Learning and prediction.
- Training and Visualising Word Vectors - Jan 23, 2018.
In this tutorial I want to show how you can implement a skip gram model in tensorflow to generate word vectors for any text you are working with and then use tensorboard to visualize them.
- Building a Wikipedia Text Corpus for Natural Language Processing - Nov 23, 2017.
Wikipedia is a rich source of well-organized textual data, and a vast collection of knowledge. What we will do here is build a corpus from the set of English Wikipedia articles, which is freely and conveniently available online.
- A Framework for Approaching Textual Data Science Tasks - Nov 22, 2017.
Although NLP and text mining are not the same thing, they are closely related, deal with the same raw data type, and have some crossover in their uses. Let's discuss the steps in approaching these types of tasks.
- 7 Types of Artificial Neural Networks for Natural Language Processing - Oct 19, 2017.
What is an artificial neural network? How does it work? What types of artificial neural networks exist? How are different types of artificial neural networks used in natural language processing? We will discuss all these questions in the following article.
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- KDnuggets™ News 17:n38, Oct 4: What Blockchains Mean to Big Data; Keras Deep Learning Cheat Sheet; Machine Learning in Finance - Oct 4, 2017.
Also: XGBoost, a Top Machine Learning Method on Kaggle, Explained; How to win Kaggle competition based on NLP task, if you are not an NLP expert; Fundamental Breakthrough in 2 Decade Old Algorithm Redefines Big Data Benchmarks
- Machine Learning Translation and the Google Translate Algorithm - Sep 14, 2017.
Today, we’ve decided to explore machine translators and explain how the Google Translate algorithm works.
- Apple: macOS Software Engineer, Natural Language Processing - Aug 10, 2017.
Seeking a Software Engineer to join the natural language processing team that drives on-device text intelligence at Apple, and work on NLP technologies that power autocorrection, predictive typing, Spotlight search, emoji prediction, and smart responses.
- 5 Free Resources for Getting Started with Deep Learning for Natural Language Processing - Jul 19, 2017.
This is a collection of 5 deep learning for natural language processing resources for the uninitiated, intended to open eyes to what is possible and to the current state of the art at the intersection of NLP and deep learning. It should also provide some idea of where to go next.
- Top 15 Python Libraries for Data Science in 2017 - Jun 13, 2017.
Since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity.
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- Text Mining 101: Mining Information From A Resume - May 24, 2017.
We show a framework for mining relevant entities from a text resume, and how to separation parsing logic from entity specification.
- AIA Group: Natural Language Processing (NLP) Engineer - May 22, 2017.
Responsible for leveraging ML and Natural Language Processing (NLP) techniques to build solutions to better insurance processes and business model benefiting both internal and external stakeholders and creating the next generation insurance platform.
- Using Deep Learning To Extract Knowledge From Job Descriptions - May 9, 2017.
We present a deep learning approach to extract knowledge from a large amount of data from the recruitment space. A learning to rank approach is followed to train a convolutional neural network to generate job title and job description embeddings.
- 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.
- 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.