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Our Research in 2016: Personal Scientific Highlights

Our Research in 2016...

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), showed that convolutional […]

Data Science Challenges

Data Science Challen...

This post is thoughts for a talk given at the UN Global Pulse lab in Kampala as part of the second Data Science in Africa Workshop at the UN Global Pulse Lab in Kampala, Uganda. It covers challenges in data science. Data is a pervasive phenomenon. It affects all aspects of our activities. This diffusiveness […]

What Donald Trump and Biased Polls Can Teach Us About Data

What Donald Trump an...

Pity the pollster.  As the election cycle mercifully nears its inevitable end, cries of bias from the trailing party will grow louder, and a sport played for well over a hundred years, calling statistics lies, reaches fever pitch. Donald Trump is, of course, correct. Survey polls are biased.   Bias is certainly nothing new to […]

Part 3: The Data Science Ecosystem, Data Applications

Part 3: The Data Sci...

Remember that quote I started part two with? About data scientists wanting better tools for wrangling so they could work on the “sexy stuff”? Well, after covering how data is stored, how its cleaned, and how its combined from disparate databases, we’re finally there. Data applications are where the “sexy stuff” like predictive analysis, data […]

Part 2: The Data Science Ecosystem, Data Wrangling

Part 2: The Data Sci...

There was a money quote from Michael Cavaretta, a data scientist at Ford Motors, in a recent article in the NY Times. The piece was about the challenges data scientists face going about their daily business. Cavaretta said: “We really need better tools so we can spend less time on data wrangling and get to […]

12 Algorithms Every Data Scientist Should Know

12 Algorithms Every ...

Algorithms have become part of our daily lives and they can be found in almost any aspect of business. Gartner calls this the algorithmic business and it is changing the way we (should) run and manage our organizations. There are all kinds of algorithms and for each aspect of your business, there are different algorithms, which […]

Churn Analytics or… How Data Science Will Become Your Marketing Team’s Best Friend

Churn Analytics or&#...

Most of the media and e-commerce Chief Data Officers I talk to on a daily basis dream of an active collaboration between their Marketing and Data Science teams. To realize this goal, we suggest setting a use case that promotes cooperation between colleagues with different skill-sets. One of our favorite cross-team approaches is to practice […]

Why Do Certain Musical Notes Sound “Good” Together?

Why Do Certain Music...

Two notes sounding “good” together sounds like a very subjective statement.  The songs we like and the sounds we like are incredibly dependent on our culture, personality, mood, etc.  

Apache Drill’s Data Science Potential

Apache Drill’s...

With the rising demand for big data analysis, several tools have been launched in the past couple of years. My unwavering love for SQL spurred me to look for analysis tools which are easier to learn/use with proficiency in SQL. I have come across Drill very recently and I am quite impressed with the flexibility […]