AdaBoost is short for Adaptive Boosting. It is basically a machine learning algorithm that is used as a classifier. Whenever you have a large amount of data and you want divide it into different categories, we need a good classification algorithm to do it. We usually use AdaBoost in conjunction with other learning algorithms to improve … Continue reading What Is AdaBoost?
Category: Machine Learning
Why Would We Ever Use Blind Search?
Over the last few decades, we have seen a lot of technologies come by and make a significant impact. Most of these technologies, if you have noticed, revolve around intelligent actions. Let's say you are in the middle of a street and you want a cab. We can solve this problem in a couple of … Continue reading Why Would We Ever Use Blind Search?
What Is Fuzzy Matching?
This is a continuation of the previous blog post on fuzzy search. We use fuzzy matching algorithms in fuzzy search to come up with the search results. The strength of a fuzzy search algorithm heavily depends on the strength of the fuzzy matching algorithm that is being used. The concept of matching refers to an … Continue reading What Is Fuzzy Matching?
What Is Fuzzy Search?
The word "fuzzy" means something that is indistinct or vague, something that cannot be explained precisely. We all know what "search" means. That should give you a hint of what this blog post is about. Whenever you type something into the Google search engine, you will see that it always returns good results, even when … Continue reading What Is Fuzzy Search?
Quantum Computing And Machine Learning
Quantum Computing refers to the use of quantum mechanical phenomena to make computations. This field is making big strides in the last decade because it can actually help us solve some of the most challenging problems in the realm of computer science, particularly in machine learning and security. Machine learning is all about building better … Continue reading Quantum Computing And Machine Learning
What Is Random Walk?
Consider the following situation. We have a drunkard who is clinging to a lamppost, and now he decides to start walking. He is in the middle of the street and the road runs from east to west. In his inebriated state, he is as likely to take a step towards the east as he is … Continue reading What Is Random Walk?
Gaussian Mixture Models
Let's say you have a lot of data and you want to estimate the underlying statistical model. Wait a minute, why on earth would I care about that? Well, if you estimate the model, then you can analyze unknown data that is not under our control. Some of the common examples would be weather estimation, … Continue reading Gaussian Mixture Models
Overfitting In Machine Learning
Let's say you are given a small set of data points. These data points can take any form like weight distribution of people, location of people who buy your products, types of smartphones, etc. Now your job is to estimate the underlying model. As in, if an unknown point comes in, you should to be … Continue reading Overfitting In Machine Learning
What Is K-Means Clustering?
Let's say you get a whole bunch of data samples and you want to do some analysis about the underlying structure of those samples. You know that they can be categorized into certain groups, but you are not exactly sure what those categories are. For example, you get the data associated with shopping behavior of … Continue reading What Is K-Means Clustering?
Bayes Point Machines
In machine learning, we use a lot of supervised learning models to analyze data and recognize patterns. If we consider the basic problem of binary classification, a machine learning algorithm takes a set of input data and predicts which of two possible classes a particular input belongs to. Kernel-classifiers comprise a powerful class of non-linear … Continue reading Bayes Point Machines
Perpetual Enigma 