Summary: There are five basic styles of recommenders differentiated mostly by their core algorithms. You need to understand what’s going on inside the box in order to know if you’re truly optimizing this critical tool.
Added by William Vorhies on January 17, 2017 at 9:20am — No Comments
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on DSC.
Added by Vincent Granville on January 17, 2017 at 8:51am — No Comments
If you’re relatively new to the NLP and Text Analysis world, you’ll more than likely have come across some pretty technical terms and acronyms, that are challenging to get your head around, especially, if you’re relying on scientific definitions for a plain and simple explanation.
We decided to put together a list of 10 common terms in Natural Language Processing which we’ve broken down in layman terms, making them easier to understand. So if you don’t know your “Bag of Words”…Continue
Added by Mike Waldron on January 17, 2017 at 1:30am — No Comments
Our article "New Comprehensive Taxonomies on Mobile Security and Malware Analysis" has been published in International Journal of Information Security Science (IJISS). The poster below summarizes the article.
The three academic taxonomies (…Continue
Added by Gürol Ca on January 16, 2017 at 11:35pm — No Comments
This tutorial describes theory and practical application of Support Vector Machines (SVM) with R code. It's a popular supervised learning algorithm (i.e. classify or predict target variable). It works both for classification and regression problems. It's one of the sought-after machine learning algorithm that is widely used in data science competitions.
What is Support Vector Machine?
The main idea of support vector machine is to…
Added by Deepanshu Bhalla on January 16, 2017 at 7:30am — No Comments
As the world is getting more tech savvy and advancements made in the information technology especially in the healthcare industry has opened areas in data mining and machine learning. Within the area of data mining one technique which has gained a lot of popularity as well as skepticism among the auditors and fraud detectives is Benford’s Law or “The Law of First digit.
In the past some researchers in Canada used the Benford’s Law distribution to detect anomalies within the claims…Continue
Added by Sunil Kappal on January 16, 2017 at 5:12am — No Comments
The growth and the profitability of small businesses depends on the customers. The customers are the source of revenue of these businesses. It is imperative to find ways of impressing them. This will guarantee customer loyalty, which results in constant flow of revenue. Collection of accurate data will help. Below are strategies of using customer data for the stability of your business.
The customers are the ones using your services or products. Their reasons for…Continue
Added by Isabella Rossellini on January 15, 2017 at 9:00pm — No Comments
Data isn't your business.It's just by-product of doing business.I know you want to get rid of those redundant data which suck up a lot of storage space.From years companies are known to pay extra to eradicate waste leftover from the production process.Times have changed, though. Through genius innovation, many entrepreneurs have taken what was once useless sludge and transmuted it into massive profits.
After yielding their finished product, breweries in the late 19th…Continue
Added by vivek upadhyay on January 15, 2017 at 9:30am — No Comments
Added by Sandeep Raut on January 15, 2017 at 7:00am — 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 January 14, 2017 at 9:00am — No Comments
I have been writing about the Crosswave Differential Algorithm for a number of years. I described in previous blogs how the algorithm emerged almost by accident while I was attempting to write an application intended to support quality control. In this blog I will be discussing the event model that powers the…Continue
Added by Don Philip Faithful on January 14, 2017 at 5:27am — No Comments
Contributed by David Richard Steinmetz. He enrolled in the NYC Data Science Academy 12-week full time Data Science Bootcamp program taking place between July 5th to September 23rd, 2016. This post is based on their third project - Web Scraping, due on 6th week of the program. The original article can be found here.
Added by SupStat on January 13, 2017 at 2:30pm — No Comments
Big Data has truly come of age in 2013 when Oxford English Dictionary introduced the term “Big Data” for the first time in its dictionary. That of course begs the question ‘When was the term Big Data first used and Why?’. My curiosity led me to lot of research material but I relied mostly on Mr. Gil Press’s “A Very Short History of Big data” from Forbes, Mr. Steve Lohr’s “The Origins of ‘Big Data': An Etymological Detective Story“ from The New York Times, Mr. Mark van Rijmenam’s “A Short…Continue
Added by Ramesh Dontha on January 13, 2017 at 8:00am — No Comments
Big data and analytics are proving to be a great way to bring about positive results regarding operations. Even though the success of a business still relies on keeping the customer happy, it's no secret that social media and new technology have a hand in it. This is why analytics is such a great option when improving upon relationships with the customer.
1. Utilize Social and Mobile Roles
When a company wants to find out what their…Continue
Added by Sasha Brown on January 13, 2017 at 5:23am — No Comments
Here is our new selection of featured articles and resources posted since Monday.Continue
Added by Vincent Granville on January 12, 2017 at 10:22am — No Comments
2016 has been a prolific year for Machine Learning/AI companies in all fronts. In this post I have tried to capture some notable funding rounds and acquisitions of Machine Learning (ML) startups that took place last year. Admittedly there are too many of these events and I have probably missed some, but I am reasonably certain that I have covered a good chunk of them. Before jumping to the table below, I would like to cover some general themes first:
1. Companies involved…Continue
Added by Al Gharakhanian on January 11, 2017 at 7:40pm — No Comments
This article was posted by Ankit Gupta.
If there is one language, every data science professional should know – it is SQL. SQL stands for Structured Query Language. It is a programming language used to access data from relational databases.
We conducted a skilltest to test our community on SQL and it gave 2017 a kicking start. A total of 1666 participants registered for the skilltest.
Added by Emmanuelle Rieuf on January 11, 2017 at 11:30am — No Comments
This could a little late given that we have already embarked upon a new year. But it could be worthwhile looking back for a moment...
2016 was definitely the year of AI in the recent technology timeline. If that’s a little far fetched, considering the wide use of drones, advances in VR/AR and blockchain, that’s because of the ‘bias’ (read enthusiasm) in my neurons. I haven’t been for long in this field but after Deepmind’s paper a few years back, this year was…Continue
Added by Anurag Priyadarshi on January 11, 2017 at 4:00am — No Comments
Would you like to know how much they’re spending, when they’re spending,…Continue
Added by Mark Ross-Smith on January 11, 2017 at 3:31am — No Comments