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?
Tag: Artificial Intelligence
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?
What Are Conditional Random Fields?
This is a continuation of my previous blog post. In that post, we discussed about why we need conditional random fields in the first place. We have graphical models in machine learning that are widely used to solve many different problems. But Conditional Random Fields (CRFs) address a critical problem faced by these graphical models. … Continue reading What Are Conditional Random Fields?
Why Do We Need Conditional Random Fields?
This is a two-part discussion. In this blog post, we will discuss the need for conditional random fields. In the next one, we will discuss what exactly they are and how do we use them. The task of assigning labels to a set of observation sequences arises in many fields, including computer vision, bioinformatics, computational … Continue reading Why Do We Need Conditional Random Fields?
Expectation Maximization
Probabilistic models are commonly used to model various forms of data, including physical, biological, seismic, etc. Much of their popularity can be attributed to the existence of efficient and robust procedures for learning parameters from observations. Often, however, the only data available for training a probabilistic model are incomplete. Missing values can occur which will … Continue reading Expectation Maximization
Robot Vs Turing
In one of my previous blog posts, we discussed about measuring computer's intelligence and how we can use the Turing test for it. After Turing proposed that test, a lot of people realized its importance and started working on it. People really wanted to believe that machines are indeed capable of thinking. We need a … Continue reading Robot Vs Turing
The Genesis Of Genetic Algorithms
Let's say you have a function and you want to optimize it. In real life, this function can take many forms like choosing the right set of features for your car while keep the price low, picking the best possible apartment considering all the different factors like location, rent, closeness to stores etc, making a … Continue reading The Genesis Of Genetic Algorithms
