# An Overview of Linear Regression Models
Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data.
Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data.
An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data. An autoencoder learns two functions: an encoding function that transforms the input data, and…
The Boosted Trees Model is a type of additive model that makes predictions by combining decisions from a sequence of base models. Gradient Boosted Machine (GBM) is one of the most effective machine…
Tree-based models use a decision tree to represent how different input variables can be used to predict a target value. Machine learning uses tree-based models for both classification and regression…
A descriptive statistic is a summary statistic that quantitatively describes or summarizes features from a collection of information, while descriptive statistics is the process of using and…
In machine learning, support vector machines are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. In this post, we will go…
The world of computers is moving fast. While going through some materials on algorithms, I have come across an interesting discussion -enhancements in hardware (cpu) vis-a-vis algorithms. One side of…
Two simple maths puzzles! In the first problem we prove a well known property of prime numbers. In the second one, we are just trying to get shortest path on a chess board.
Given an alphanumeric string, find the shortest substring that occurs exactly once as a contiguous substring in it. Overlapping occurrences are counted as distinct. If there are several candidates of…
A simple puzzle based on algebra and arithmetics.