This is part of a new series of articles: once or twice a month, we post previous articles that were very popular when first published. These articles are at least 6 month old but no more than 12 month old. The previous digest in this series was posted here a while back. Below is our third edition.… Continue
Added by Vincent Granville on September 27, 2016 at 8:00am —
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.
- As businesses incorporate massive volumes of Internet of Things (IoT) and digital data, they've turned to modern architectures that include Hadoop data lakes for cost-effective storage and…
Added by Vincent Granville on September 24, 2016 at 9:30am —
There's a lot of literature on learning the technical aspect of data science: statistics, machine learning, data munging, big data. This material will serve you well when starting out or working under a lead. But what about when you are ready to spread your wings and lead a project yourself or embark on a project independently? Here you need a different sort of storytelling - the type that communicates why you are working on a project, what the value is, and what you have accomplished.… Continue
Added by Brian Rowe on September 23, 2016 at 1:30pm —
Most academic papers and blogs about machine learning focus on improvements to algorithms and features. At the same time, the widely acknowledged truth is that throwing more training data into the mix beats work on algorithms and features. This post will get down and dirty with algorithms and features vs. training data by looking at a 12-way…
Added by Leena Kamath on September 23, 2016 at 12:00pm —
We talk a lot about making decisions based on data but we need to be careful about how hard and fast those decisions are. Our decisions are only as good as our data and our analysis.
Neither can be perfect. Data is always a sample of the full… Continue
Added by Andrew Patricio on September 23, 2016 at 9:00am —
The Real-Time Crime Forecasting Challenge seeks to harness the advances in data science to address the challenges of crime and justice. It encourages data scientists across all scientific disciplines to foster innovation in forecasting methods. The goal is to develop algorithms… Continue
Added by Emmanuelle Rieuf on September 23, 2016 at 8:30am —
Digging through messy data and doing numerous calculations just so you can submit a report or arrive at the result of your quarterly business development can sometimes be nigh impossible. After all, we are only human, and by the time we get to the other side of our spreadsheet equation, we have… Continue
Added by Dante Munnis on September 23, 2016 at 3:00am —
There are lots of writings about how data analytics changes business and everything, but deep down it only matters how you put these analytics in action. This is a software engineering perspective.
Following the success of AlphaGo, the machine learning software that defeated the Go master Lee Sedol, the Wired magazine released an article titled … Continue
Added by Jari Turkia on September 22, 2016 at 8:30pm —
This article was written by Fjodor Van Veen.
With new neural network architectures popping up every now and then, it’s hard to keep track of them all. Knowing all the abbreviations being thrown around (DCIGN, BiLSTM, DCGAN, anyone?) can be a bit overwhelming at first.
So I decided to compose a cheat sheet containing many of those architectures. Most of these are neural networks, some are completely different beasts. Though all of these architectures are presented as novel and… Continue
Added by Emmanuelle Rieuf on September 21, 2016 at 2:30pm —
This article was written by Joseph Rickert.
We all "know" that correlation does not imply causation, that unmeasured and unknown factors can confound a seemingly obvious inference. But, who has not been tempted by the seductive quality of strong correlations?…
Added by Emmanuelle Rieuf on September 21, 2016 at 2:30pm —
My favorite quote on Big Data is by Dan Ariely who says "Big Data is like teenage sex, everyone talks about it, no one really knows how to do it, everyone things everyone else is doing it, so everyone claims that they are doing it..."
Dan Ariely's views aside, Gartner defines Big Data as " high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.”
Added by Mark Sharma on September 21, 2016 at 11:00am —
These articles were all posted in the last few days:
Added by Vincent Granville on September 21, 2016 at 7:30am —
This article was written by Hannah Augur. Hannah is a writer, editor and nerd based in Berlin. She's a researcher with knowledge and work in a variety of fields, including 3D printing, fantasy video games and even coffee manufacturing.
“Big data” and “data science” may be some of the bigger buzzwords this decade, but they aren’t necessarily new concepts. The idea of data science spans many different fields, and has been slowly making its way into the… Continue
Added by Emmanuelle Rieuf on September 20, 2016 at 3:30pm —
This article was posted by Roger Huang. Roger Huang heads up growth and marketing at Springboard. He broke into a career in data by analyzing $700 million worth of sales for a major pharmaceutical company. Now he writes content that compiles insights from Springboard's network of data experts to help others do the same.
Data science… Continue
Added by Emmanuelle Rieuf on September 20, 2016 at 10:00am —
Summary: Are there large, sustainable career opportunities in AI and if so where? Do they lie in the current technologies of Deep Learning and Reinforcement Learning or should you focus your career on the next wave of AI?
If you’re a data scientist thinking about… Continue
Added by William Vorhies on September 20, 2016 at 7:33am —
Printed electronics are being vouched as the next best thing in Internet of Things (IoT), the technology that is rightly regarded as a boon of advancing technology. Silicon-based sensors are the first that have been associated with IoT technology. These sensors have numerous applications, such as track data from airplane, wind turbines, engines, and medical devices, amongst other internet connected devices.…
Added by Khusro Khan on September 20, 2016 at 12:30am —
Contributed Article from MIT Professor Devavrat Shah.
According to analyst firm IDC, the amount of data being generated in our digital universe is expected to double every two years, producing more than 40,000… Continue
Added by Vincent Granville on September 19, 2016 at 8:57am —
The idea and concept of “Big Data” has been around for a while now, however it seems there are many people who still believe it is shrouded in mystery. Therefore, in the following post we are going to debunk some of the top big data…
Added by Martin Doyle on September 19, 2016 at 1:30am —
One of the most significant characteristics of the evolving digital age is the convergence of technologies. That includes information management (databases), data… Continue
Added by Kirk Borne on September 18, 2016 at 9:00am —
In this year of Rudolf Kalman’s demise, this article is dedicated to his memory.
We introduce a new Machine Learning (ML) solution for Dynamical, Non-linear, In-Stream Analytics. Clearly, such a solution will accommodate Static, Linear and Offline (or any combination thereof) Machine Learning tasks. The value of such a solution is significant because the same… Continue
Added by PG Madhavan on September 18, 2016 at 8:00am —