Summary: To ensure quality in your data science group, make sure you’re enforcing a standard methodology. This includes not only traditional data analytic projects but also our most advanced recommenders, text, image, and language processing, deep learning, and AI projects.
A Little History…
Added by William Vorhies on July 26, 2016 at 9:15am —
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.
- Explore how government agencies are using predictive analytics to solve real-world problems at the sixth annual…
Added by Vincent Granville on July 23, 2016 at 9:00am —
The online world isn't as simple as we've thought it to be. Behind the seemingly quiet and vast space of nothingness, huge amounts of data are uploaded and downloaded in fractions of a second. Data science does not only keeps track of these numbers, but also attempts to analyze and organize them. Algorithms are created to keep tabs on searches in search engines, analyze user data preference, and so on and so forth.
The demand for qualified data scientists have become very… Continue
Added by Sagar Mandan on July 22, 2016 at 4:00am —
Tips by 4 DataHack Winners
Nalin Pasricha, DataHack Rank 1
Nalin is an investment banker turned data scientist who currently works as an independent consultant.
He has participated in 17 hackathons at DataHack. He won Data Hackathon 3.x and emerged as the 1st Runner Up in Black Friday DataHack.
Here’s what Nalin has to say:
- Our mind works…
Added by Sukanya Mohapatra on July 21, 2016 at 10:00pm —
Unlike traditional application programming, where API functions are changing every day, database programming basically remains the same. The first version of Microsoft Visual Studio .NET was released in February 2002, with a new version released about every two years, not including Service Pack releases. This rapid pace of change forces IT personnel to evaluate their corporation’s applications every couple years, leaving the functionality of their application intact but with a completely… Continue
Added by Irina Papuc on July 21, 2016 at 3:00pm —
In my recent blog, Marrying Kalman Filtering & Machine Learning, we saw the merger of Bayesian exact recursive estimation (algorithm for which is Kalman Filter/Smoother in the linear, Gaussian case) and Machine Learning. We developed a solution called Kernel Projection Kalman Filter for business applications that… Continue
Added by PG Madhavan on July 21, 2016 at 2:06pm —
Here is our Thursday selection - all were posted and featured today.
Added by Vincent Granville on July 21, 2016 at 9:30am —
This two part blog is based on my forthcoming book: Data Science for Internet of Things.
It is also the basis for the course I teach Data Science for Internet of Things Course. I will be syndicating sections of… Continue
Added by ajit jaokar on July 21, 2016 at 7:57am —
Big data, this flood of data that scares some people, has moved from hype to reality. However, collecting more data does not always mean better insights. The exponential data growth via social networks and soon by connected objects tomorrow has become big challenges. The cursor should now be on the exploitation of useful data; or somebody call it Smart Data. How to achieve this mission to make intelligent data? Please see the Big Data posts from… Continue
Added by Jason Li on July 21, 2016 at 5:20am —
Can Pre-hire Talent Assessments Be a Part of a Predictive Talent Acquisition Strategy?
Over the past 30+ years, businesses have spent billions on talent assessments. Many of these are now being used to understand job candidates. Increasingly, businesses are asking how (or if) a predictive talent acquisition strategy can include the use of pre-hire…
Added by PIYASHI BHATTACHARYYA on July 21, 2016 at 5:00am —
Many of us have to handle web based projects that are used in production, which provide various services to the public. When dealing with such projects, it is important to be able to build and deploy our code quickly. Doing something quickly often leads to errors, especially if a process is repetitive, therefore it’s a good practice to automate such a process as much as possible.
My fellow developers: There is no excuse for… Continue
Added by Irina Papuc on July 20, 2016 at 9:00pm —
While Deep Learning has shown itself to be very powerful in applications, the underlying theory and mathematics behind it remains obscure and vague. Deep Learning works, but theoretically we do not understand much why it works. Some leading machine learning theorists like Vladimir Vapnik criticise Deep Learning for its ad-hoc approach that gives a strong flavour of brute force rather than technical sophistication. Deep Learning is not theory intensive; it is empirical based more (hence… Continue
Added by Syed Danish Ali on July 20, 2016 at 5:00am —
Angular 2 takes a web component-based approach to building powerful applications for the web. It is used along with TypeScript which provides support for ECMAScript 5, ECMAScript 6, and ECMAScript… Continue
Added by Anil Singh on July 19, 2016 at 7:00pm —
Summary: If you’re running a Data Science Team you need to be thinking about efficiency and productivity. Those solutions can take the form of management and process, but there are also some new tools you should be evaluating.
In our last article we talked about some organizational principles and tips for increasing the productivity of your data science team. Those ideas were in the realm of management and process. You can tell that our… Continue
Added by William Vorhies on July 19, 2016 at 10:41am —
Contributed by Joseph Wang. He is currently in the NYC Data Science Academy 12 week full time Data Science Bootcamp program taking place between April 11th to July… Continue
Added by SupStat on July 19, 2016 at 10:30am —
When you Google “Kalman Filter AND Machine Learning”, very few interesting references pop up! Perhaps my search terms are not the best, perhaps Fintech guys keep such algorithms close to their vests, perhaps there is not much of work done in bringing these two incredibly powerful tools together...
In any case, Part II of my new book, “Systems Analytics: Adaptive Machine Learning workbook” focuses exactly on this merger.
I am happy to report that pre-publication copy… Continue
Added by PG Madhavan on July 18, 2016 at 7:24am —
Ableism (able + ism) is apparent in many interactions between people. While driving on a road having a posted limit of 60 KPH, I was traveling slower since I expected a red light to soon appear ahead of me. The driver behind me - at that point stopped due to the red light - hollered that no car should be driving less than the posted limit. I explained, "60 is the maximum speed. You shouldn't do more than the… Continue
Added by Don Philip Faithful on July 16, 2016 at 6:27am —
Pretty much every data rookie starts with Excel. It is a wonderful program for storing, cleaning and analysing (yes, you read that correctly) your data.
Strictly speaking, Excel isn’t free, but really – who pays for it these days? If you buy a Windows PC or laptop it’ll usually come pre-installed, and if you get a new PC at work your employer will have it pre-installed for you. If you’re prepared to look the other way, there are guys who know guys who can get you a copy that fell off… Continue
Added by Lee Baker on July 15, 2016 at 6:19am —
Machines and tools used in complex industrial procedures, as well as the ones used for daily purposes, have advanced considerably in the recent past. Smart machines are intelligent devices or equipment that use… Continue
Added by Khusro Khan on July 15, 2016 at 2:30am —
The gender of artificial intelligence
By Tyler Schnoebelen,
There’s Apple’s Siri, Microsoft’s Cortana, Amazon’s Alexa, and Nuance’s Nina. Sure, Facebook has “M”, Google has “Google Now”, and Siri’s voice isn’t always that of a woman. But it does feel worth noting that (typically male-dominated) engineering groups routinely give women’s names to the things you issue commands to. Is artificial…
Added by Leena Kamath on July 14, 2016 at 9:21am —