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Deep Learning Research Review Week 3: Natural Language Processing
This is the 3rd installment of a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summarizing and explaining research papers in specific subfields of deep learning. This week focuses on applying deep learning to Natural Language Processing. The last post was Reinforcement Learning and the post before was Generative... Read more
Data Visualization for Situational Awareness
When you look at the image below, do you feel a sense of urgency? It would be surprising if you did. This is showing a user interface for a transmission control room where operators monitor and manage power grids. Although it may not seem like it, there’s a big problem... Read more
Visual Analytics of Instagram’s #gopro hashtag with AI
Images have become a very common medium of human expression on the internet with the coming up of social networks. Facebook is the biggest repository of digital images ever. This trend is only going to intensify given the emergence of image first platforms like Instagram and Snapchat, also called “Visual... Read more
What Makes a Good Data Visualization – a Data Scientist perspective
Data visualization has been a subject of many thousands of books, courses, and blogs. My course on data mining included a one-hour lecture on Data Visualization. However, since you, my reader, don’t have an hour to read this blog, here is a KDnuggets-sized summary of what makes a good data visualization from... Read more
Visualising Similarity: Maps vs. Graphs
The visualization of complex data sets is of essential importance in communicating your data products. Beyond pie charts, histograms, line graphs and other common forms of visual communication begins the reign of data sets that encompass too much information to be easily captured by these simple data displays. A typical... Read more
Tides of Information Flow: Visualizing Our Digitally-Mediated Reality
I consume a lot of news, especially recently. But often I feel like I have a hard time grasping the shape of it. What is different this time? What am I missing? What have I learned? Where did that other thing go? I’m also interested in maps. So, I built this:... Read more
Our research in 2016: personal scientific highlights
Year 2016 has been productive for science in my team. Here are some personal highlights: bridging artificial intelligence tools to human cognition, markers of neuropsychiatric conditions from brain activity at rest, algorithmic speedups for matrix factorization on huge datasets… Artificial-intelligence convolutional networks map well the human visual system Eickenberg et al (preprint),... Read more
Deep Learning Research Review Week 2: Reinforcement Learning
This is the 2nd installment of a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summarizing and explaining research papers in specific subfields of deep learning. This week focuses on Reinforcement Learning. Last time was Generative Adversarial Networks ICYMI Introduction to Reinforcement Learning 3... Read more
Deep Learning Research Review Week 1: Generative Adversarial Nets
This week, I’ll be doing a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summarizing and explaining research papers in specific subfields of deep learning. This week I’ll begin with Generative Adversarial Networks.  Introduction According to Yann LeCun, “adversarial training is the coolest thing... Read more
Regular Expression & Treemaps to Visualize Emergency Department Visits
It’s been a while since my last post on some TB WHO data. A lot has happened since then, including the opportunity to attend the Open Data Science Conference (ODSC) East held in Boston, MA. Over a two day period I had the opportunity to listen to a number of leaders in... Read more

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