 ## The Math Behind ID3 Decision Tree Algorithm

Hello, welcome to ID3 decision tree algorithm’s overview lecture Suppose that this is a data set that we are going to work on There are three different features in this dataset and one decision class. These are features, and class is the target value target value. there are, as seen, 14 instances and the decision […] ## The Math Behind C4.5 Decision Tree Algorithm

Hello, welcome to C4.5 decision tree algorithm’s overview video. actually, it is very similar to ID3 algorithm. You might remember that we have calculated entropy and information gain for features … in ID3. Here, … We are going to calculate additional metrics. In this way, we can normalize … the calculations of C4.5. This additional […] ## Machine Learning – Supervised Learning – Understanding Different Evaluation Models

Hello! In this video, we’ll look at understanding different evaluation models The previous evaluation models were geared towards classification. Now, we’ll talk more about the model evaluation metrics that are used for regression. Evaluation metrics provide a key role in the development of a model, as it provides insight to areas that require improvement. There […] ## Machine Learning – Supervised Learning Regression Algorithms

Hello! In this video, we’ll be covering Regression Algorithms Regression originated from Statistical Modelling. And since Machine learning is a much newer concept, it has adopted Regression analysis. Regression outputs a response that is ordered and continuous. The output consists of one or more continuous variables There are many different types of regression. The most […] ## How Artificial Neural Network (ANN) Algorithm Work | Data Mining | Introduction to Neural Network

let’s understand harder the neural network model work for this we are going to understand backward propagation algorithm and in this process we are going to understand several terms like case updating batch updating hard weight and bias updates and then intuitive understanding of why it works then we are going to understand the stopping […] ## Experiment Database for Machine Learning Tutorial – Graphical Querying

Hi, my name is Joaquin Vanschoren and this is a tutorial on querying the experiment database for machine learning. The experiment database is a large database which collects experiments with data mining algorithms. It runs them on different datasets, under different parameter settings and if I have a question I can just answer that question […] ## You Ask, I Answer: Best Language for Marketing Data Science, R or Python?

Christopher Penn: IBM. In today’s episode, Maria asks, which is the best language to learn from marketing data science, R or Python? So the answer to this question depends, it depends on a bunch of different things. Number one, what you’re going to be doing if we’re talking pure data science where you’re going to […] ## Machine Learning – Hierarchical Clustering

Hello! In this video, we’ll be measuring the distances between clusters using algorithms for hierarchical Clustering. Let’s look at some algorithms for Hierarchical Clustering. The first type we’ll look at is Agglomerative Clustering. Remember that agglomerative clustering is a bottom-up approach. Let’s say our dataset has n data points. First, we want to create n […] ## Machine Learning – Supervised Learning – Advantages & Disadvantages of Decision Trees

Hello! In this video, we’ll be covering the advantages and disadvantages of Decision Trees Let’s begin by examining the advantages and disadvantages of using a decision tree? The first main advantageof using a decision tree is that it’s easy to understand and, as such, requires little data preparation. A decision tree also runs in logarithmic […] ## Machine Learning – Supervised Learning Classification

Hello! In this video, we’ll be covering Classification. The concept of categorizing data is based off of training with a set of data so that the machine can essentially learn boundaries that separate categories of data. Therefore, new data inputted into the model can be categorized based on where the point exists. Imagine that you […]