I thought that this interview deserved a repost here at Data Science Central. It is with the man responsible for Artificial Intelligence at Facebook: the AI director Yann Lecun; and might be of interested and appeal to the knowlegeable of AI here.
I post an excerpt and the link below for the full interview:
IEEE Spectrum: We read about Deep Learning in the news a lot these days. What’s your…Continue
Added by Nuno Fernandes on March 5, 2015 at 8:00am — No Comments
The term ‘Big Data’ is a massive buzzword at the moment and many say big data is all talk and no action. This couldn’t be further from the truth. With this post, I want to show how big data is used today to add real value.
Eventually, every aspect of our lives will be affected by big data. However, there are some areas where big data is already making a real difference today. I have categorized the application of big data into 10 areas where I see the most widespread use as well as…Continue
Submitted by Kendall Brennan, from Halo BI. Originally posted here.
Try introducing yourself as a Competitive Intelligence or CI analyst. Chances are that the reactions will range from (a) That's what you do all day, Google search? to (b) Identifying 007 ways to look at competition, Corporate Bond?
Of course, one can always resort to the classical definition of CI. It is defined as the action of defining, gathering, analyzing,and distributing intelligence about products, customers,…Continue
The full version is always published Monday. Starred articles or sections are new additions or updated content, posted between Thursday and Sunday.
Added by Vincent Granville on March 4, 2015 at 4:00pm — No Comments
Before Los Angeles Times reporter Laurie Becklund died of metastatic breast cancer earlier this month, she wrote a powerful final column. She asked friends and family not to say that she died fighting a courageous battle, a meaningless, trite phrase. She excoriated the pink ribbon and…Continue
Added by Peter Bruce on March 4, 2015 at 3:00pm — No Comments
Guest blog post by Tom Fawcett. Originally posted on SVDS.
Tom Fawcett is Principal Data Scientist at Silicon Valley Data Science. Co-author of the popular book Data Science for Business, Tom has over 20 years of experience applying machine learning and data mining in practical applications. He is a veteran of companies such as Verizon and…Continue
NOTE: This post can be more beautifully read via Medium here: Why Everyone Needs to Learn to Code
Creating a data extractor is usually simple in the mind of a developer, although in reality it’s usually not so simple. Data extraction as a concept is fairly straightforward: Get the data from A and copy it to destination B. However, as most developers know, the devil is in the detail.
The comparison is performed on a data set where linear regression works well: salary offered to a candidate, based on programming language requirements in the job ad: Python, R or SQL. This is a follow-up to the article highest paying programming skills. The increased accuracy of linear regression estimates is negligible, and well below the noise level…Continue
This blog is a review of two books. Both are available for free from the MapR site, written by Ted Dunning and Ellen Friedman (published by O Reilly) : About Time Series Databases: New ways to store and access data and…Continue
Added by ajit jaokar on March 1, 2015 at 9:22am — No Comments