Natural Language Processing Guide: 30 Free ODSC Resources to Learn NLP
NLP, as with many other topics within data science, involves many skills, tools, languages, frameworks, and more. The ODSC Guide to Natural Language Processing is our compendium of 20 free resources for you to get started with NLP, including videos from past ODSC NLP presentations, tutorials, articles, and more.... Read more
10 Notable Frameworks for NLP
Natural Language Processing hit its big stride back in 2017 with the introduction of Transformer Architecture from Google. State of the art approaches helped bridge the gap between humans and machines and helped us build bots capable of using human language undetected. It’s an exciting time. You’re going to... Read more
State-of-the-art NLP Made Easy with AdaptNLP
Andrew and Brian are speakers for ODSC East 2020 this April 13-17 in Boston. Be sure to check out their talk, “State-of-the-art NLP Made Easy,” there! Natural Language Processing (NLP) has advanced significantly since 2018, when ULMFiT and Google’s release of the BERT language model approached human-level performance on... Read more
Level Up: spaCy NLP for the Win
Kimberly is a speaker for ODSC East 2020! Be sure to check out her talk, “Level Up: Fancy NLP with Straightforward Tools,” there! Natural language processing (NLP) is a branch of artificial intelligence in which computers extract information from written or spoken human language.  This field has experienced a... Read more
Introduction to Spark NLP: Foundations and Basic Components
Veysel is a speaker for ODSC East 2020 this April 13-17! Be sure to check out his talk, “Spark NLP for Healthcare: Lessons Learned Building Real-World Healthcare AI Systems,” there! * This is the first article in a series of blog posts to help Data Scientists and NLP practitioners... Read more
The Most Influential NLP Research of 2019
Natural language processing (NLP) is one of the most important technologies to arise in recent years. Specifically, 2019 has been a big year for NLP with the introduction of the revolutionary BERT language representation model. There are a large variety of underlying tasks and machine learning models powering NLP... Read more
Text Classification in Python
This article is the first of a series in which I will cover the whole process of developing a machine learning project. This one focuses on training a supervised learning text classification model in Python. The motivation behind writing these articles is the following: as a learning data scientist who has... Read more
9 Organizations and People Leading the NLP Field
Got a keen interest in where NLP is headed? Who doesn’t? It’s one of the most exciting developments we have in AI, and it’s making waves in every industry imaginable. If you’re trying to keep up with all the advancements, we’ve got nine leaders in NLP you need to... Read more
What do Data Scientists and Decision Makers Need to Know About Google’s BERT
Any data scientist will tell you that one of the most challenging parts of natural language processing projects is the lack (or shortage) of training data. With deep learning, this has been semi-solved, but now the problem can be too much data—up to millions or even billions of training... Read more
State-of-the-Art Natural Language Understanding at Scale
For many of you in data science, natural language processing is a critical component of your projects. David Talby of Pacific.ai is here to introduce Apache Spark’s new NLP library and outline how it can facilitate your NLP pipeline for higher accuracy and faster results using the same amount... Read more