Summary: We’re rapidly approaching the point where AI will be so pervasive that it’s inevitable that someone will be injured or killed. If you thought this was covered by simple product defect warranties it’s not at all that clear. Here’s what we need to start thinking about.
Added by Vincent Granville on December 9, 2018 at 3:30pm — No Comments
The goal of both logical and physical architecture specifications is to define and document the logical and physical components of a system, respectively, in order to provide clarity around how those component elements relate to one another. The artifacts resulting from either effort could be text documentation, or diagrams, and both have their own advantages and drawbacks.
This is an extract is taken from …Continue
Added by Packt Publishing on December 6, 2018 at 12:47am — No Comments
With the introduction of big data, the need for its storage increased gradually. Companies were focussing on building solutions and frameworks to store as much data as possible. When this problem is addressed by big names such as Hadoop, companies shifted their focus on data processing. Here, the popular term that everyone might have heard once is “data science.” Undoubtedly, data science is considered as the future of AI…Continue
Added by Ritesh Patil on December 6, 2018 at 2:00am — No Comments
In this article, I hope to inspire you to start exploring satellite imagery datasets. Recently, this technology has gained huge momentum, and we are finding that new possibilities arise when we use satellite image analysis. Satellite data changes the game because it allows us to gather new information that is not readily available to businesses.
Added by Michał Frącek on December 6, 2018 at 2:30am — No Comments
Updated on Dec 12, 2018. An error was fixed when g(x) is not equal to x, and a new section "Generalization" was added. A link to a large collections of intriguing integrals was added at the bottom, in the "Related Problems" section.
Below are a few integrals that you won't find in textbooks. Solving them is a good exercise for college students with some advanced calculus training. We provide the solution, as well as a general framework to compute many similar integrals. Maybe…Continue
Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (graphical and quantitative) to better understand data. It is easy to get lost in the visualizations of EDA and to also lose track of the purpose of EDA. EDA aims to make the downstream analysis easier.…Continue
Added by ajit jaokar on December 6, 2018 at 5:49am — No Comments
My writing engagement at Data Science Central came up unexpectedly. Back in August 2018, I stumbled upon an excellent write-up on Data Science Central. The author, Bill Vorhies, shared his thoughts on career transitioning toward data science. I wrote him an email, complimenting him on his blog post, and I dropped a few lines about my own transition. Here's his response:
"Congratulations on your remarkable journey. Perhaps you’d like to write one or more articles…Continue
We are in the process of writing and adding new material (compact eBooks) exclusively available to our members, and written in simple English, by world leading experts in AI, data science, and machine learning. In the upcoming months, the following will be added:
It’s that time of year again when I look into the Crystal Skull…er, ball, and make some predictions of the continuing challenges and new trends I foresee in Big Data and Data Science for the coming year.
Digital Transformation moves beyond just…Continue
Added by Bill Schmarzo on December 5, 2018 at 8:43am — No Comments
On 3 Dec 2018 when the US treasury yield curves inverted (a short-term US government bond yield is higher than its long-term yield), Economists quickly warned the stock market of an impending economic slowdown or even a recession. The following…Continue
Added by Zhongmin Luo on December 5, 2018 at 1:00am — No Comments
Recommender systems use algorithms to provide users with product or service recommendations. Recently, these systems have been using machine learning algorithms from the field of artificial intelligence. An increasing number of online companies are utilizing recommendation systems to increase user interaction and enrich shopping potential. Use cases of recommendation systems have been expanding rapidly. They across many aspects of…Continue
Added by Divya Singh on November 20, 2018 at 8:30pm — No Comments
In this 5 Minute Analysis we'll focus on exploring the collection of Kaggle datasets data in real-time, reorganizing it, and filtering the data to find popular datasets with many downloads but very few kernels.
Added by Benjamin Waxer on November 8, 2018 at 9:00am — No Comments
Emerging cloud applications like machine learning, AI and big data analytics require high performance computing systems that can sustain the increased amount of data processing without consuming excessive power. Towards this end, many cloud operators have started adopting heterogeneous infrastructures deploying hardware accelerators, like FPGAs, to increase the performance of computational intensive tasks. However, most hardware accelerators lack…Continue
Added by Chris Kachris on November 6, 2018 at 7:00am — No Comments
Big data is all the rage, but simply collecting it won't help much. These data visualization tools help you make sense of it all.
The rise of big data has ushered in the era of data-driven decision-making.
Vast volumes of data constantly flowing in from multiple sources contain valuable insights that can lead to better business decisions and competitive advantage. The challenge for businesses is to spend less time setting up, collecting, and organizing data, and…Continue
Added by Justin Runyon on November 23, 2018 at 12:30am — No Comments
R is a software programming language developed in 1993. In New Zealand, two professors of Auckland University Ross Ihaka and Robert Gentleman first conceived R. The most stable beta version of R was made in 2000. Here ‘R’ holds an extensive catalog produced of statistics and graphics methods. These methods include a machine learning algorithm, time series, linear regression, statistical inferences and many more.…Continue
Added by Raghavarao on November 26, 2018 at 8:30pm — No Comments
When it comes to Data Science, the most recurring topic is modeling. Quite a few articles out there talk about data preparation and only a bunch about how to communicate your results properly. However, there are hardly any dealing with the topic that we are going to cover today: data enrichment.Continue
Added by Juraj Kapasny on December 3, 2018 at 1:30am — No Comments
By Gunnar Carlsson
December 3, 2018
Added by Jonathan Symonds on December 4, 2018 at 3:00pm — No Comments
Summary: Sales is supposed to be an area that is more immune to replacement by AI than many others because of the high level of impromptu and improvisational human contact required. That remains true. But AI is showing that it can be a valuable augment to B2B sales and some early adopters are scoring big gains.
Added by William Vorhies on December 4, 2018 at 9:59am — No Comments
Summary: There is a great hue and cry about the danger of bias in our predictive models when applied to high significance events like who gets a loan, insurance, a good school assignment, or bail. It’s not as simple as it seems and here we try to take a more nuanced look. The result is not as threatening as many headlines make it seem.
Added by William Vorhies on June 5, 2018 at 8:00am — No Comments