Starred articles are candidates for the picture of the week. A comprehensive list of all past resources is found here. We are in the process of automatically categorizing them using indexation and automated tagging…Continue
Added by Vincent Granville on October 26, 2016 at 7:30am — No Comments
Guest blog post by Jen-Hsun Hunag, Founder, President and CEO at NVIDIA, Originally entitled "The Intelligent Industrial Revolution".
Intelligent machines powered by AI computers that can learn, reason and interact with people are no…Continue
Added by Vincent Granville on October 25, 2016 at 5:00pm — No Comments
The health area is characterized by the management of huge data volumes. What if those data are processed and provided to the health professionals and their patients or, even to the health system at large? Not only one, two, three…Continue
Added by Ernesto Mislej on October 25, 2016 at 7:37am — No Comments
Data integration requires merging date from different sources, stored using technologies. Companies build a “data warehouse where aggregated data can be stored and retrieved. This is particularly useful for researchers looking to big data to aid in their investigation and corporations usually during…Continue
Added by Dante Munnis on October 25, 2016 at 7:00am — No Comments
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 fourth edition.…Continue
Added by Vincent Granville on October 24, 2016 at 5:00pm — No Comments
Summary: Convolutional Neural Nets are getting all the press but it’s Recurrent Neural Nets that are the real workhorse of this generation of AI.Continue
Added by William Vorhies on October 24, 2016 at 3:53pm — No Comments
Recently, in a previous post, we reviewed a path to leverage legacy Excel data and import CSV files thru MySQL into Spark 2.0.1. This may apply frequently in…Continue
Added by Marc Borowczak on October 23, 2016 at 5:57am — No Comments
This article was written by Ariful Mondal. Artful is a senior manager, data science and big data analytics consultant at Tata Consultancy Services.
This is an attempt to showcase some worked out examples of Machine Learning (ML) use German Credit Data. Though we have selected credit…Continue
Added by Emmanuelle Rieuf on October 22, 2016 at 9:30am — No Comments
Whilst you are online, everything is about transfer of data – thus, emails and web pages are basically a file that when you read or log onto, you are in essence downloading the file or transferring it to your screen so you can view it. If you watch a film or play a game online, these activities send data backward and forward in…Continue
Added by Glen Johnson on October 22, 2016 at 9:30am — No Comments
A theme in my blogs is how the "structure" of data - rather than just the "content" - affects what that data can say and is capable of doing. In particular, I suggest that certain structures tend to reinforce certain contents; this means that a structural imposition can have an effect similar to a contextual…Continue
Added by Don Philip Faithful on October 22, 2016 at 5:30am — No Comments
This post is a brief review of leading Data Integration tools in the market. Heavily referencing from the Gartner 2016 report and peer reviews from my circle.
The data integration tool market was worth approximately $2.8 billion at the end of 2015, an increase of 10.5% from the end of 2014 [2016 Gartner Report – Data Integration Tools].
Key data integration responsibilities-
Added by Kashif Saiyed on October 21, 2016 at 7:30pm — No Comments
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.
Added by Vincent Granville on October 21, 2016 at 12:00pm — No Comments
Added by SupStat on October 21, 2016 at 9:30am — No Comments
This set of blog posts is part of the book/course on Data Science for the Internet of Things. We welcome your comments atjjb at cantab dot net. Jean-Jacques Bernard has been a founding member of the Data Science for Internet of Things Course.
Please email at ajit.jaokar at futuretext.com if you are interested in joining the course.
You can find the first…
Added by Jean-Jacques Bernard on October 19, 2016 at 11:30pm — No Comments
Here is our updated list of top Data Science Central (DSC) resources, including reference articles and tutorials, top categories, tools and techniques, as well as several useful links (jobs, events, training, webinars, books and so on) and information about our popular newsletter. You will also find information about blogging with us, or where to find us on Facebook, LinkedIn or Twitter.
Added by Vincent Granville on October 19, 2016 at 8:00pm — No Comments
Added by Khosrow Hassibi on October 19, 2016 at 10:00am — No Comments
Understanding that big data comes from such a huge pool of devices, constantly collecting new data, gives you an idea where security threats may come from. Each device that is online, from phones to tablets to computers to smart appliances, has the potential of…Continue
Added by Shezagary on October 18, 2016 at 9:30pm — No Comments
This reference is a part of a new series of DSC articles, offering selected tutorials, references/resources, and interesting articles on subjects such as deep learning, machine learning, data science, deep data science, artificial intelligence, Internet of Things, algorithms, and related topics. It is designed for the busy reader who does not have a lot of time digging into long lists of advanced publications.…Continue
Added by Vincent Granville on October 18, 2016 at 7:30pm — No Comments
This article was written by Jason Brownlee. Jason is the editor-in-chief at MachineLearningMastery.com.He has a Masters and PhD in Artificial Intelligence, has published books on Machine Learning and has written operational code that is running in production.
After you make predictions, you need to know if they are any good.
There are standard measures that we can use to summarize how good a set of predictions actually are.
Knowing how good a set of predictions is,…
Added by Emmanuelle Rieuf on October 18, 2016 at 10:30am — No Comments
Many people new to data science might believe that this field is just about R, Python, Hadoop, SQL, and traditional machine learning techniques or statistical modeling. Below you will find fundamental articles that show how modern, broad and deep the field is. Some data scientists are actually doing none of the above. In my case, I don't even code, but instead, I make various applications talk to each other, in a machine-to-machine communication framework. It is true though that most data…Continue
Added by Vincent Granville on October 18, 2016 at 9:00am — No Comments