– Hi everyone. I’m Priya Natarajan; I am the current director of the Franke Program in Science and the Humanities, and I would like to give a warm welcome to our first talk of the academic year. Our talk today is part of the continuing series on mapping and knowing,… Continue Reading Mapping the Frontier between Man and Machine

Hi! Welcome back to Data Mining with Weka. In the last lesson, we looked at classification by regression, how to use linear regression to perform classification tasks. In this lesson we’re going to look at a more powerful way of doing the same kind of thing. It’s called “logistic regression”.… Continue Reading Data Mining with Weka (4.4: Logistic regression)

Hello again. In this lesson, 3.4, we’re going to carry on looking at association rules and the Apriori algorithm. We left off last lesson looking at an itemset with 3 items and a support of 4, which means that there are 4 instances in the dataset for which those conditions… Continue Reading More Data Mining with Weka (3.4: Learning association rules)

Today we’re going to revise logic gates first of all AND, OR and NOT Let’s take a look to AND, first of all I am going to write out a so called a truth table in my old way which it might be slightly different to the way other people… Continue Reading AND OR NOT – Logic Gates Explained – Computerphile

Hello, again! Last time we learned a little bit about what distributed Weka is and a little bit about the MapReduce framework. In this lesson, we’re going to install distributed Weka and start to use some of the components that come with it. So, let’s get started. Okay, here we… Continue Reading Advanced Data Mining with Weka (4.2: Installing with Apache Spark)

Hello! Welcome to Class 2 of Advanced Data Mining with Weka. My name is Albert Bifet. I’m a member of the Weka machine learning group, and I work at Telecom ParisTech in Paris, France. In this class, we’re going to talk about data stream mining in Weka and MOA. Data… Continue Reading Advanced Data Mining with Weka (2.1: Incremental classifiers in Weka)

Hello! In the last lesson, we installed distributed Weka and ran our first distributed Weka for Spark job that analyzed and computed a header for the hypothyroid dataset. In this lesson, we’ll take a closer look at how these jobs are configured, and we’ll run a few more jobs that… Continue Reading Advanced Data Mining with Weka (4.3: Using Naive Bayes and JRip)

Hello again! In data mining, people are always asking “how much data do I need?” We’re going to show you how you can address that question in this lesson using learning curves. The advice on evaluation from “Data Mining with Weka” was: if you’ve got a large, separate test set,… Continue Reading More Data Mining with Weka (5.3: Learning curves)

I mean Data mining is you get a lot of Information in a lot of raw data and you want to get the nuggets of information? Hence the word mining, so the Golden the data. That’s the Data Mining I usually starts with people saying oh You got loads of… Continue Reading Nuggets of Data Gold – Computerphile

Hello, I will explain how SVM algorithm works. This video will explain the support vector machine for linearly separable binary sets Suppose we have this two features, x1 and x2 here and we want to classify all this elements You can see that we have the class square and the… Continue Reading How SVM (Support Vector Machine) algorithm works