Predictive Analytics with Microsoft Azure Machine Learning is authored by Roger Barga, Valentine (Val) Fontama, and Wee Hyong Tok. This post provides a review to inform a purchase decision for this book from publisher Apress. Click here to see the book on Amazon.
PASS Summit is a paid conference in Seattle, WA from November 5 to 7, 2014 (some preconference sessions precede the conference on November 3 and 4, and have an additional charge). The purpose of this blog post is to provide a guide to the PASS Summit for people interested in data science. To support this goal, this post has both a slide deck and YouTube video (16 minutes).
Today, Microsoft is announcing and offering general availability for Azure Machine Learning. Many of the features are listed at http://azure.microsoft.com/en-us/services/machine-learning/
With this launch, I will be releasing more information on this new technology as the service becomes more available to the public. This blog post has the links and information to get started in three steps.
Yesterday, Microsoft publicly announced a new technology for machine learning called Microsoft Azure Machine Learning. This cloud-based technology promises ease in building data-driven analytics applications. Based on my MVP status and relationship with key Microsoft people, I have been aware of this technology for about two years: I have been keeping silent on this topic and will be only commenting on what is publicly available as it becomes available. This blog post has more of the publicly-announced details.
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I have been a SAS programmer and architect for years: I did my first professional work in the 1990s. I also have made friends among people who focus on SAS. I had mentioned in a SAS Consultants forum in Google Groups that the open source Julia language was delivering impressive results compared with the R language. The testing involves several math problems which could be translated into most any language. Previous results (and code) has been already shared on http://julialang.org/
I had wanted to try SAS to see how it does against Julia, but I did not have a machine where I could load both software applications. However, Dom Pazzula not only tested it on his machine, but also provided the comparison code. This blog post has the results of the test and the SAS code for you to try the comparison yourself.
Microsoft Program Manager Eric Ligman has been posting lists of free eBooks from his blog. I have not mentioned these books in past blog postings. So, this posting is a catch-up for the three lists he has already mentioned and subsequently summarized. I will be commenting on free books which help for Microsoft data analytics and data science.
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I was recently asked this question by someone who works for Microsoft, and who was sincerely trying to understand the differences. I first used SPSS in the early 1990s on the mainframe, just after I had started using SAS on UNIX. Over my career, I have seen SPSS in different environments, and I also published a paper once about SPSS options for stratified sample analysis (previously those functions were not available but now they are available as an option).
This post will have my response on how to evaluate SPSS versus SQL Server Data Mining.
I will be speaking at the second Charlotte BI Edition SQL Saturday (in Charlotte, NC) on October 19. I will be at the PASS Summit as a volunteer (previous to the SQL Saturday), but will be talking at this Saturday conference about data mining. This post has the details.
I am honored to be speaking on the PASS (Professional Association for SQL Server) track at this year’s Silicon Valley Code Camp (in Los Altos Hills, CA). Annually, this user event is (currently) the largest Code Camp in the United States. Also, I have been a presenter at some past SQL Saturday events in Mountain View, and I know that passion for data mining runs deep in this technology hub. This post has details on the two presentations I will be giving.
I am happy to be a sponsor (via MarkTab Inc) and presenter at SQL Saturday 226 South Florida. I have been to this event in the past, and many of my presenter friends will also be at this excellent event. Also, I will giving away some great prizes: five passes (value US$1495) for data mining training to be held on September 10-12, 2013 (winners must be present at the end of the event to win). I also will be giving three separate one-hour presentations, two on data mining, and one for professional development. This blog post has the details, and links to the presentations.
I copresented (with Artus Krohn-Grimberghe) a session called “A Best Practices Framework for Data Mining” for the June 13, 2013 PASS Virtual Business Analytics Group. This talk marks my third for this relatively new group, and I’m glad to work with leader Melissa Demsak on these quality presentations. For this talk, we had about 40 people, and seamlessly delivered the talk from both North America (myself) and Europe (Artus, who is in Germany). This post has the details and the links to the slides and recorded presentation.
MarkTab Inc. is a sponsor for SQL Saturday 220, Atlanta, GA (May 18), and will be giving away five passes to the three-day Experience Data Mining training on September 10-12, 2013. I will also be presenting two topics at SQL Saturday: first, Secrets of Enterprise Data Mining, and second, Applied Enterprise Semantic Mining. This post has the details.