Support Vector Machines are machine learning model used for classification and regression analysis. SVM is basically the representation of examples as the points in a graph such that representation of separate category is divided by a wide gap that gap ...
Stacking is an ensemble machine learning technique that allows combining different prediction models to make a single model that make the final prediction out of the provided dataset. Sometimes these combined models can be same depending up to the type ...
Scikit-learn is probably the most useful library for machine learning in Python. The sklearn library contains a lot of efficient tools for machine learning and statistical modelling including classification, regression, clustering, model selection, preprocessing and dimensionality reduction. The predefined modules ...
Introduction From predicting winners in an election such as exit polls to building recommendation systems, Data Science plays a vital role in every industry. We know that there is a vast advancement in technology these days with the growth of ...
What comes in your mind when you hear the word Facebook? Friends, Entertainment, Chats, that’s all we commonly think of, when we use Facebook. Facebook is one big hub of people from different age groups and country. According to a ...
Classification is a type of supervised learning. It specifies the class to which data elements belong to and is best used when the output has finite and discrete values. It predicts a class for an input variable as well. There ...
Artificial Intelligence system is often defined because of the study of the rational agent and its environment. The agents sense the environment through sensors and act on their environment through actuators. An AI agent can have mental properties like knowledge, ...
In this article, we are going to talk about the support vector machine(also known as SVMs) algorithm in machine learning. Support vector machine is one of the most common and widely used algorithms in machine learning. It is a supervised ...
A regression model is basically a representation of a set of independent quantity on a unit dependent quantity, that dependent quantity in machine learning is our output value produced from the set of input that is independent values or records. ...
Before we hop into the derivation of simple linear regression, it’s important for us to have a very strong intuition on what we are actually going to do and especially why we are going to do it? With that being ...
