Introduction to Clinical Natural Language Processing
Andrew is a speaker for ODSC West 2019! Be sure to check out his talk, “Healthcare NLP with a doctor’s bag of notes,” this November in San Francisco! Doctors have always written clinical notes about their patients — originally, the notes were on paper and were locked away in... Read more
Essential NLP Tools, Code, and Tips
In a previous article, we introduced the influential impact of natural language processing (NLP) in different industries and explained the way this discipline is reshaping several fields, yet facing huge challenges on its way. The main drawbacks we face these days with NLP tools relate to the fact that... Read more
An Introduction to Natural Language Processing (NLP)
Everything we express (either verbally or in written) carries huge amounts of information. The topic we choose, our tone, our selection of words, everything adds some type of information that can be interpreted and value can be extracted from it. In theory, we can understand and even predict human... Read more
NLP is Changing More Than Just Business: Applications of NLP in History, Art, and Higher Ed
Natural language processing (NLP) is affecting more than just your chatbot experience. It has broad-reaching applications in any field where data is king. Here’s a hint: that’s every field. You may not expect NLP to transform fields outside business and finance, but considering how much data humans have produced... Read more
Why Word Vectors Make Sense in Natural Language Processing
If you’re up-to-date with progress in natural language processing research, you’ve probably heard of word vectors in word2vec. Word2vec is a neural network configuration that ingests sentences to learn word embeddings, or vectors of continuous numbers representing individual words. The... Read more
An Idiot’s Guide to Word2vec Natural Language Processing
Word2vec is arguably the most famous face of the neural network natural language processing revolution. Word2vec provides direct access to vector representations of words, which can help achieve decent performance across a variety of tasks machines are historically bad at. For a quick examination of how word vectors work,... Read more
Tracking the Progress in Natural Language Processing
This post introduces a resource to track the progress and state-of-the-art across many tasks in NLP. Go directly to the document tracking the progress in NLP. Research in machine learning and in natural language processing (NLP) is moving so fast these days, it is hard to keep up. This... Read more
Sentiment Analysis in R Made Simple
Sentiment analysis is located at the heart of natural language processing, text mining/analytics, and computational linguistics. It refers to any measurement technique by which subjective information is extracted from textual documents. In other words, it extracts the polarity of the expressed sentiment in a range spanning from positive to... Read more
The Art of Building a Chatbot
With the development of deep learning and NLP chatbots become more and more popular. The hype for chatbots is already high and it will be increasing for the next several years. “By 2020, over 50% of medium to large enterprises will have deployed product chatbots” — Van Baker, research vice president... Read more
NLP: Extracting the Main Topics from your Dataset Using LDA in Minutes
I recently started learning about Latent Dirichlet Allocation (LDA) for topic modelling and was amazed at how powerful it can be and at the same time quick to run. Topic Modelling is the task of using unsupervised learning to extract the main topics (represented as a set of words)... Read more