Read my previous post to understand how K-Means algorithm works. In this post I will try to run the K-Means on Iris dataset to classify our 3 classes of flowers, Iris setosa, Iris versicolor, Iris virginica (our classess) using the flowers sepal-length, sepal-width, petal-length and petal-width (our features) Getting data: describe the data: Converting the class […]
Category: Artificial Intelligence
Mathematics behind K-Mean Clustering algorithm
K-Means is one of the simplest unsupervised clustering algorithm which is used to cluster our data into K number of clusters. The algorithm iteratively assigns the data points to one of the K clusters based on how near the point is to the cluster centroid. The result of K-Means algorithm is: K number of cluster […]
Understanding Support vector Machines using Python
Support Vector machines (SVM) can be used for both classification as well as regression tasks but they are mostly used in classification applications. Some of the real world applications include Face detection, Handwriting detection, Document categorisation, SPAM Filtering, image classification and protein remote homology detection. For many researchers, SVM is the first best choice for […]
Maths behind Polynomial regression
Polynomial regression is a process of finding a polynomial function that takes the form f( x ) = c0 + c1 x + c2 x2 ⋯ cn xn where n is the degree of the polynomial and c is a set of coefficients. Through polynomial regression we try to find an nth degree polynomial function which is the closest approximation of our data points. Below is a sample random dataset which has been regressed […]
Evaluating the fitness of a modal with a cost function
Previously we derived a simple linear regression modal for our Pizza price dataset. We built a modal that predicted a price of $13.68 for a 12 inch pizza. When the same modal is used to predict the price of an 8 inch pizza, we get $9.78 which is around $0.78 more than the known price of $9. […]
Math behind Linear Regression with Python code
Simple linear regression is a statistical method you can use to study relationships between two continuous (quantitative) variables: independent variable (x) – also referred to as predictor or explanatory variable dependant variable (y) – also referred to as response or outcome The goal of any regression model is to predict the value of y (dependant variable) based on the […]
Finally some success after an year of research in trying to teach a computer how to understand a question like a human.
Like I always believed, there is a way to represent each and every natural language sentence using mathematical notations. Its been an year since I have been playing around with various AI algorithms and after countless failed attempts today I made some progress. A sentence can be divided into three parts as explained in Subject-Verb-Object. So a good AI who […]
Markow chain explained in simple words
Markow chain is a probabilistic process used to predict the next step based on the probabilities of the existing related states. Its called a chain because the probability of the next step is dependant on the other steps in the group. For example, if the weather is cloudy then its highly likely that it might rain (The next […]
How about inventing a language easy for both humans and bots to understand
English or any other language as a matter of fact is difficult for a computer to understand, especially when the meaning is ambiguous. Most chat bots are “if else” programs that do nothing more than basic NLP or pattern recognition. Not denying how useful they have been lately but we still have miles to go. […]
Language is a representation of Thought
Mathematics is the language of God and so is the language of our mind. A man may speak many languages but there is only one way of storing everything he speaks. Below is probably how information from the external world coming inside is stored. As proposed by Noam Chomsky in Universal Grammar, the L.A.D, […]