When we talk about deep neural networks, we tend to focus on feature learning. Traditionally, in the field of machine learning, people use hand-crafted features. What this means is that we look at the data and build a feature vector which we think would be good and discriminative. Once we have that, we train a model … Continue reading Autoencoders In Machine Learning
Tag: Pattern Recognition
What’s The Importance Of Hyperparameters In Machine Learning?
Machine learning is becoming increasingly relevant in all walks of science and technology. In fact, it’s an integral part of many fields like computer vision, natural language processing, robotics, e-commerce, spam filtering, and so on. The list is potential applications is pretty huge! People working on machine learning tend to build models based on training data, … Continue reading What’s The Importance Of Hyperparameters In Machine Learning?
What Is A Markov Chain?
If you have studied probability theory, then you must have heard Markov's name. When we study probability and statistics, we tend to deal with independent trials. What this means is that if you conduct an experiment a lot of times, we assume that the outcome of one trial doesn't influence the outcome of the next … Continue reading What Is A Markov Chain?
What Is Manifold Learning?
Machine learning is being used extensively in fields like computer vision, natural language processing, and data mining. In many modern applications that are being built, we usually derive a classifier or a model from an extremely large data set. The accuracy of the training algorithms is directly proportional to the amount of data we have. … Continue reading What Is Manifold Learning?
Recognizing Shapes Using Point Distribution Models
In the field of computer vision, we often come across situations where we need to recognize the shapes of different objects. Not only that, we also need our machines to understand the shapes so that we can identify them even if we encounter them in different forms. Humans are really good at these things. We somehow … Continue reading Recognizing Shapes Using Point Distribution Models
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?
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?
Perpetual Enigma 