Technologies in the field of data science are progressing at an exponential rate. The introduction of Machine Learning has revolutionized the world of data science by enabling computers to classify and comprehend large data sets. Another important innovation which has changed the paradigm of the world of the tech world is Artificial Intelligence (AI). The two…Continue
Added by Ronald van Loon on June 14, 2017 at 7:00am — No Comments
During a random talk with a friend of mine, I was told an observation that most of the well-known Hollywood personalities are born between the month of April and July. This made me curious and did a random search for few actors, and it seemed like most of them were born between those months but couldn't say it for sure so went ahead and wrote a script to fetch the date of birth data for the top 5,000 ranked male and female movie personalities in IMDB which is a total of 10,000 movie…Continue
After my first post on Anomaly Detection for Time Series post, I would like to continue presenting what I did during the course at for the Data Science for IoT Course at Department of Continued Education of the University of Oxford with Ajit Jaokar.
In line with what I wrote previously, this second post will be about predictive maintenance.
The post is divided into…
Added by Jean-Jacques Bernard on June 13, 2017 at 10:00pm — No Comments
Everyone gets sunk by office politics at some point in their career, but data scientists are in some ways especially ill-prepared to navigate the unspoken rules and hidden agendas that together form a critical part of the corporate world. Although some people may actively fuel office politics to gain power, I'll assume that's not the case for most of us. I'd like instead to simply suggest a few basic survival skills, so we can focus as much as possible on…Continue
Summary: Quantum computing is already being used in deep learning and promises dramatic reductions in processing time and resource utilization to train even the most complex models. Here are a few things you need to know.
Added by William Vorhies on June 13, 2017 at 8:00am — No Comments
Added by ajit jaokar on June 13, 2017 at 5:00am — No Comments
We recently set-out to build a massive list of AI companies from around the world. This was a dataset that included companies with just seed funding all the way to the likes of Amazon and Google.
The information we put together included:
Company Information: address & phone number
Products/Services offered: description of each product or service
Added by Utsav on June 12, 2017 at 5:30pm — No Comments
The world is long past the Industrial Revolution, and now we are experiencing an era of Digital Revolution. Machine Learning, Artificial Intelligence, and Big Data Analysis are the reality of today’s world.
I recently had a chance to talk to Ciaran Dynes, Senior Vice President of Products at Talend and Justin Mullen, Managing Director at…Continue
Added by Ronald van Loon on June 12, 2017 at 7:00am — No Comments
As of late, advertisement spending as a major aspect of aggregate showcasing cost has expanded. The purpose behind this is accuracy. With the support of better than ever information, and in addition dynamic…Continue
Added by Johny Basha on June 12, 2017 at 1:00am — No Comments
R language is the world's most widely used programming language for statistical analysis, predictive modeling and data science. It's popularity is claimed in many recent surveys and studies. R programming language is getting powerful day by day as number of supported packages grows. Some of big IT companies such as Microsoft and IBM have also started developing packages on R and offering enterprise version of R.
Added by Deepanshu Bhalla on June 12, 2017 at 12:30am — No Comments
Guest blog by Annalee Newitz
Annalee Newitz is the Tech Culture Editor at Ars Technica. Her work focuses on cultural impact of science and technology. She founded the science and science fiction blog io9.com, and is the author of Scatter, Adapt, and Remember: How Humans Will Survive a Mass Extinction. Her first novel, Autonomous, comes out in September 2017. She has a Ph.D. in English and American Studies from UC Berkeley,…Continue
Added by Shay Pal on June 11, 2017 at 1:00pm — No Comments
As an analyst, our first reaction when we get the data to analyse is to ask an ETA. Then we plan to attack the data left-right-centre and crush the maximum juice out of it with an exhaustive list of analysis techniques.
Oh dear, we got it all wrong!
This approach might get 50 slides to present the analysis but would miss on the most crucial aspect of any analytics engagement: a buy-in from the business folks. Because, since the start, the target of the whole analysis was data,…Continue
While many organizations are creating tremendous value from the IoT, some organizations are still struggling to get started. It has now become one of the key element of Digital Transformation that is driving the world…
Added by Sandeep Raut on June 10, 2017 at 10:30pm — 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 June 10, 2017 at 8:30am — No Comments
This article is no longer available. For new resources about learning Python, follow this link.…
Many organizations are associating data monetization with selling their data. But selling data is not a trivial task, especially for organizations whose primary business relies on its data. Organizations new to selling data need to be concerned with privacy and Personally Identifiable Information (PII), data quality and accuracy, data transmission reliability, pricing, packaging, marketing, sales, support, etc. Companies such as Nielsen, Experian and Acxiom are…
Added by Bill Schmarzo on June 10, 2017 at 5:30am — No Comments
This shinyapp is a live shiny/R web application (hosted on shinyapps.io) that implements simple sentiment analysis POC with R, to have an insight about the people's sentiment about the smartphones from different brands released in India for a couple of weeks over a past time period, it was written a few years back (in 2014), for demonstration purpose, with the tweets…Continue
Here I discuss four interesting mathematical problems (mostly involving famous unsolved conjectures) of considerable interest, and that even high school kids can understand. For the data scientist, it gives an unique opportunity to test various techniques to either disprove or make progress on these problems. The field itself has been a source of constant innovation -- especially to develop distributed architectures, as well as HPC (high performance computing) and quantum computing to try to…Continue
Added by Vincent Granville on June 9, 2017 at 12:30pm — No Comments
Data science can be a lucrative career path, with plenty of opportunities to forge your way up the ladder. In order to get there, however, first you have to start at the bottom. Here’s how to take the first steps along that path.
Get an education
You won’t be able to get a job in data science if you can’t demonstrate the skills…Continue
In this article, the clustering output results using Spectral clustering (with normalized Laplacian) are going to be compared with taht obtained using KMeans clustering on a few shape datasets.
The following couple of slides taken from the Coursera Course: Mining Massive Datasets by Stanford University
describe the basic concepts behind…