Kaggle is an AirBnB for Data Scientists – this is where they spend their nights and weekends. It’s a crowd-sourced platform to attract, nurture, train and challenge data scientists from all around the world to solve data science and predictive analytics problems through machine learning. It has over 536,000 active members from 194 countries and it receives close to 150,000 submissions per month. Started from Melbourne, Australia Kaggle moved to Silicon Valley in 2011, raised some 11…Continue
Added by Zeeshan Usmani on September 17, 2017 at 4:00am — No Comments
Drones flying in the skies to deliver packages to customers, is how technology based on data and analytics is likely to impact retail industry and consumers both – in near future. New ways and means of understanding the customers are emerging and both, online and offline retailers are embracing this data first strategy. These retailers are trying their level best to match customers to products and services.
Retail is increasingly becoming a data driven…Continue
Added by Chirag Shivalker on September 16, 2017 at 11:00am — 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 September 16, 2017 at 8:30am — No Comments
This is our third post of a new series featuring articles published long ago. We manually selected articles that were most popular or overlooked, time-insensitive (for instance we eliminated articles about data science products because software packages and platforms have evolved so much over the last few years) and we only kept articles that still make sense and are useful today. Our previous edition …Continue
Summary: Performance comparison for the popular Deep Learning frameworks supported by Keras – TensorFlow, CNTK, MXNet and Theano
If there are any doubts in regards to the popularity of Keras among the Data Scientist/Engineer community and the mindshare it commands, you just need to look at the support it has been receiving from all major AI and Cloud players. Currently the official Keras release already supports Google's TensorFlow and Microsoft's CNTK deep…Continue
Here is our selection of featured articles and resources posted since Monday. We had numerous high quality articles submitted this week!Continue
Added by Vincent Granville on September 14, 2017 at 8:00am — No Comments
Equestrian sports is one of the oldest forms of sports entertainment. Its history can be dated back to the ancient Greek civilization. Since then, the trots have transcended the periodical barriers from time to time, walking stride to stride with the age-specific customs, and entertaining the crowds in the process. And,…Continue
Columnar storage is a familiar data storage technique that is used by many data warehousing products because of its high effectiveness in many computing scenarios. The technique is usually a synonym of high-performance within the industry.
But is columnar storage a perfect strategy? A google shows that criticisms surrounding it are mainly about data modification. There are few discussions of its application to the read-only data analysis and computing, which will be taken care…Continue
Added by JIANG Buxing on September 12, 2017 at 11:00pm — No Comments
MLaaS is neither new nor rocket science or an unknown service. In today’s time there are hundreds of companies in this domain which are working as a service provider of MLaaS (SPMLaaS). Machine learning is into so many services and applications as on date and we may not even aware of them or most of them. In the area of…Continue
Added by Vinod Sharma on September 12, 2017 at 10:00pm — No Comments
While many complain about Google's increased monopoly and control over our lives, in this article, I offer a different perspective regarding Google search. I will go as far as to claim that Google's influence (as a search engine) is declining. Not that their traffic share or revenue is shrinking, to the contrary, both are probably increasing. And Google is moving in many other directions business-wise: Search might have been their first, most used and most well-known product, but the future…Continue
Added by Vincent Granville on September 12, 2017 at 7:30pm — No Comments
After Equifax's massive data breach - social security number, date of birth, and address from 143 million Americans stolen by cyber criminals - the question is: Can a financial institution be liable for using wrong Equifax data?
One would expect that this Equifax event will result in an increase in ID theft. Banks trust credit…Continue
Added by Vincent Granville on September 12, 2017 at 10:00am — No Comments
Summary: With only slight tongue in cheek about the road ahead we report on the just passed House of Representative’s new “Federal Automated Vehicle Policy” as well as similar policy just emerging in Germany. As a model of regulation on emerging AI technology we think they got this just about right.
Added by William Vorhies on September 12, 2017 at 9:35am — No Comments
In this multi-part series, we will explore how to get started with tensorflow. This tensorflow tutorial will lay a solid foundation to this popular tool that everyone seems to be talking about. The first part will focus on introducing tensorflow, go through some applications and touch upon the architecture.
This post is the first part of the multi-part series on a complete tensorflow tutorial –
DML stands for “Dynamical Machine Learning” (more in the book, “SYSTEMS Analytics for IoT Data Science”, 2017). This match is not surprising once you realize that DML & IoT are both based on the venerable Systems Theory. Let us dig deeper . . .
Consider IoT for industrial applications. A machine is instrumented with sensors, data are collected in real-time (or at intervals), communicated to the cloud where IoT Data Science…Continue
Added by PG Madhavan on September 11, 2017 at 12:30pm — No Comments
This article was written by Uli Bethke.
The full title is "Dimensional Modeling and Kimball Data Marts in the Age of Big Data and Hadoop".
Is dimensional modeling…Continue
Added by Amelia Matteson on September 11, 2017 at 11:30am — No Comments
The previous posts in this series have covered several ways that business leaders can use to understand and explore how Artificial Intelligence can impact their business. We saw that there are several key ways in which AI advances can improve human productivity in organizations. The last two articles dived into Distillation: automating…Continue
Added by Roy Wilds, PhD, PHEMI Systems on September 11, 2017 at 6:00am — No Comments
The following problem appeared as an assignment in the coursera course Algorithm-I by Prof.Robert Sedgewick from the Princeton University few years back (and also in the course cos226 offered at Princeton). The problem definition and the description is taken from the course website and lectures. The original assignment was to be done in java, where in this article both the java and a corresponding python implementation will…Continue
Added by Sandipan Dey on September 11, 2017 at 4:30am — No Comments
Human life is highly unpredictable, and in order to mitigate the ill effects of this unpredictability, the concept of insurance was born. As the world around is getting more complex and advanced, the rising intensity of unpredictability is not only boosting the insurance sector but also making things more challenging and difficult for the business enterprises in this sector. Thankfully, and analytics visualization are coming forward as potential game changers in the sector and enabling…Continue
Added by Shantanu Chaturvedi on September 11, 2017 at 3:30am — No Comments
In this Digital age, every organization is trying to apply machine learning and artificial intelligence to their internal and external data to get actionable insights which will help them to be closer to today’s customer. A few years back it was the field only for data scientists and statisticians,…
Added by Sandeep Raut on September 10, 2017 at 11:30pm — No Comments
Who’s this article for:
This blog is intended for enterprise data analysts, line of business users, and data practitioners who work with qualitative and quantitative data in decision-making.
How enterprise currently use data science and business intelligence today
Quantitative analytics based on statistical models predict outcome with data models built from historical datasets using machine-learning algorithms
Added by Sing Koo on September 10, 2017 at 4:00pm — No Comments