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  • PASS SQL Saturday #687 Slovenia 2017

    Here we go for the fifth time! The leading event dedicated to Microsoft SQL Server in Slovenia, PASS SQL Saturday #687, will take place on Saturday, December 9th 2017, at the Faculty of Computer and Information Science of the University of Ljubljana, Večna pot 113, Ljubljana (https://www.fri.uni-lj.si/en/about-faculty/how-to-reach-us). This is ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on July 11, 2017
  • Embrace R @ SQL Nexus 2017 & SQL Saturday #626

    R is the hottest topic in SQL Server 2016. If you want to learn how to use it for advanced analytics, join my seminar at SQL Nexus conference on my 1st in Copenhagen. Although there is still nearly a month before the seminar, there are less than half places still available. You are also very welcome to visit my session Using R in SQL Server, Power ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on April 2, 2017
  • Data Mining Algorithms – Logistic Regression

    It’s been awhile since I wrote the last blog on the data mining / machine learning algorithms. I described the Neural Network algorithm. In addition, it is a good time to write another post in order to remind the readers of the two upcoming seminars about the algorithms I have in Oslo, Friday, September 2nd, 2016, and in Cambridge, Thursday, ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on August 31, 2016
  • DevWeek 2016 BI in SQL Server 2016 Workshop Setup

    I got some questions about virtual machine / notebook setup for my Business Intelligence in SQL Server 2016 DevWeek post-conference workshop. I am writing this blog because I want to spread this information as quickly as possible. There will be no labs during the seminar, no time for this. However, I will make all of the code available. ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on April 15, 2016
  • Data Mining Algorithms – Neural Network

    A neural network is a powerful data modeling tool that is able to capture and represent complex input/output relationships. The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform "intelligent" tasks similar to those performed by the human brain. Neural ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on January 26, 2016
  • Data Mining Algorithms – Decision Trees

    Decision Trees is a directed technique. Your target variable is the one that holds information about a particular decision, divided into a few discrete and broad categories (yes / no; liked / partially liked / disliked, etc.). You are trying to explain this decision using other gleaned information saved in other variables (demographic data, ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on October 29, 2015
  • Data Mining Algorithms – Naive Bayes

    I am continuing with my data mining and machine learning algorithms series. Naive Bayes is a nice algorithm for classification and prediction. It calculates probabilities for each possible state of the input attribute, given each state of the predictable attribute, which can later be used to predict an outcome of the predicted attribute based on ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on September 9, 2015
  • Data Mining Algorithms – Pluralsight Course

    This is a bit different post in the series about the data mining and machine learning algorithms. This time I am honored and humbled to announce that my fourth Pluralsight course is alive. This is the Data Mining Algorithms in SSAS, Excel, and R course. besides explaining the algorithms, I also show demos in different products. This gives you even ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on July 30, 2015
  • Data Mining Algorithms – EM Clustering

    With the K-Means algorithm, each object is assigned to exactly one cluster. It is assigned to this cluster with a probability equal to 1.0. It is assigned to all other clusters with a probability equal to 0.0. This is hard clustering. Instead of distance, you can use a probabilistic measure to determine cluster membership. For example, you can ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on May 12, 2015
  • Data Mining Algorithms – K-Means Clustering

    Hierarchical clustering could be very useful because it is easy to see the optimal number of clusters in a dendrogram and because the dendrogram visualizes the clusters and the process of building of that clusters. However, hierarchical methods don’t scale well. Just imagine how cluttered a dendrogram would be if 10,000 cases would be shown on ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on April 17, 2015
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