What exactly is “IoT”? Internet of Things, yes; but what does that mean?
Internet of Things is a structural definition; it says there are “Things” such as sensors and devices (on machines or people) connected together in a Network. So what? What does a Network of Sensors & Devices allow us to DO? What is the functional description of IoT?
Being able to connect things together is “table stakes” at the intelligence augmentation game. What…Continue
Added by PG Madhavan on October 16, 2016 at 9:30am — No Comments
Last year I started developing a Face Recognition model. I started with static pictures and using Wolfram Mathematica. This year I found out we can do the same job using OpenCV in Python, or creating specific filters in R and applying Weierstrass and Gaussian transformation.
There are lots of difficulties in recognizing faces of the same person, like: position, rotation of face, age, feeling, brightness, gamma, contrast, gamma, saturation, obstacles like hands,hair and so…Continue
Added by Rubens Zimbres on October 15, 2016 at 4:00am — 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 October 14, 2016 at 5:00pm — No Comments
At first there were a lot of different opinions, but now, almost everybody agrees that big data was able to take over the whole business world. A lot of businesses are relying on it and improving the tools they use for taming big data on a daily basis. They all agree that the importance of big data is huge and that everyone who wants to stay competitive in the business world…
Added by Ivan Dimitrijevic on October 14, 2016 at 3:00am — No Comments
Response Modeling Using Machine Learning Techniques with R-Programming (WIP). I have tried to exhibit credit scoring case studies with German Credit Data.
This article includes detail programming of predictive modeling
1. Univariate And Bi-Variate Analysis
2. Information Value and Weight Evidence to access prediction power of variables
3. Multivariate Analysis and Dimension Reduction using Variable Clustering
4. Different Machine Learning Techniques and their…
Added by Ariful Islam Mondal on October 13, 2016 at 10:30am — No Comments
In the previous post of our Understanding machine learning series, we presented how machines learn through multiple experiences. We also explained how, in some cases, human beings are much better at interpreting data than machines. In many tasks machines still can’t replace humans, who understand surrounding reality better and can make more accurate decisions.
Machines can be given a…Continue
Added by Algolytics on October 13, 2016 at 4:30am — No Comments
The ability to recognize objects and their relationships is at the core of intelligent behavior. This, in turn, depend on one’s ability of perceiving similarity or dissimilarity between objects, be physical or abstract ones. Hence, if we are interested to make computers behave with any degree of intelligence, we have to write programs that can work with relevant representation of objects and means to compute their similarities or lack thereof, i.e., dissimilarity (obviously, they are…Continue
The honeypot is a method of cybersecurity in which a bait (‘honey’) system/network is designed to emulate or act as a real system/network to divert malicious attacks upon the actual real system/network. The honeypot may act to mitigate, block, and in some cases capture the malicious behavior. The concept of the honeypot probably originated from two books, “The Cuckoos Egg” by Clifford Stoll and “An Evening with Berferd” by Bill Chewick, both describing the authors’ own personal…Continue
Added by Arshak Navruzyan on October 12, 2016 at 7:00pm — No Comments
What is Data Mining?
Data mining is an integrated application in the Data Warehouse and describes a systematic process for pattern recognition in large data sets to identify conclusions and relationships. Using statistical methods, or genetic algorithms, data files can be automatically searched for statistical anomalies, patterns or rules.
Wikipedia defines Data Mining as “Data mining is an interdisciplinary subfield of computer science. It is the computational process…Continue
Politecnico di Milano is investigating on it.
The proliferation of data and the huge potentialities for companies to turn data into valuable insights are increasing more and more the demand of Data Scientists.
But what skills and educational background must a Data Scientist have? What is its role within the organization? What tools and programming languages does he/she mostly use? These are some of the questions that the Observatory for Big Data Analytics of Politecnico di…Continue
Added by Alessandro Piva on October 12, 2016 at 8:30am — No Comments
Innovation Enterprise has compiled a top 30 list for individuals in big data that have had a large impact on the development or popularity of the industry. …Continue
Let’s take a trip down memory lane
Since the dawn of time, man has been using analytical reasoning and procured data to enhance his business. Take the example of the farmer, who plans his crop cycles on assumptions that are based on observations made, or what we may call now as data collected on the basis of the monsoon season and seed quality of the last few years. Thinking about the heat during the summer, the humidity, the…Continue
Added by Lucjan Zaborowski on October 12, 2016 at 2:30am — No Comments
How do we design a data model, how do we connect data, how do we represent information, how do we store or retrieve them ? These are all fundamental questions in data modeling but there is a common key to unlock them. You have to start by defining a primitive information resource, and then understand how one can build complex information structures on top of…Continue
Added by Athanassios Hatzis on October 12, 2016 at 12:30am — 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 11, 2016 at 7:42pm — No Comments
Contributed by Ismael Jamie Cruz. He is currently in the NYC Data Science Academy 12 week full time Data Science Bootcamp program taking place between April 11th to July 1st, 2016. This post is based on his third class project - Web Scraping (due…Continue
Added by NYC Data Science Academy on October 11, 2016 at 1:00pm — No Comments
Summary: It’s that time of the year when the major salary surveys come out. Once again it’s time for Data Scientist to take a victory lap. This year there’s a lot more detail.
Added by William Vorhies on October 11, 2016 at 7:30am — No Comments
A traditional business problem customized here to data science.
1. Identify the problem
In a prior post I outlined some thoughts on the outlook for the data analytics sector and referenced a database I prepared of analytics companies. At the time the list comprised about 400 names categorized into a number of sectors and segments.
I’ve continued to update the list since that time and it now comprises about 800 companies.
This image comes from Xkcd, a webcomic of romance, sarcasm, math, and language. Created by Randall Munroe, he is a CNU graduate with a degree in physics. Before starting xkcd, he worked on robots at NASA's Langley Research Center in Virginia.
I teach AP Statistics in China at an International school and I believe it's important to not only show my students how to do plots and inferential statistics on their TI Nspire calculators, but also in R using ggplot, dplyr, and R Markdown.…Continue