## Backpropagation

The training samples are passed through the network and the output obtained from the network is compared with the actual output. This error is used to change the weights of the neurons such that the error decreases gradually. This is done using the Backpropagation algorithm, also called backprop. Iteratively passing batches of…

## FeedForward Algorithm

## Activation Functions

An activation function helps a neural network to learn complex relationships and patterns in data. It takes in the output signal from the previous cell and converts it into some form that can be taken as input to the next cell. The activation function introduces non-linearity into the output of a neuron….

## Artificial Neural Network

Artificial Neural networks(ANN’s) are the base or functional unit of deep learning. A neural network emerged from a very popular machine learning algorithm named perceptron. A Neuron is the basic unit of computation in a neural network. It is also called as a node or unit. The leftmost layer in this network is…

## Perceptron

## What is Deep Learning?

## Support Vector Machines

A support vector machine (SVM) is a supervised machine learning model which can be used for both classification and regression. But they have been extensively used for solving complex classification problems such as image recognition, voice detection etc. SVM algorithm outputs an optimal hyperplane that best separates the tags. The hyperplane is a boundary that…

## Confusion Matrix

A confusion matrix is a fundamental tool in the field of machine learning and data science, often used to assess the performance of classification models. It provides a detailed breakdown of the model’s predictions compared to the actual ground truth, allowing us to evaluate various aspects of model performance. The…

## Correlation vs Causation

Introduction In the quest to understand relationships between variables, two terms consistently surface correlation and causation. Despite their apparent similarity, they have different implications and uses. This distinction is more than just a technicality; it’s a fundamental concept that every data analyst or scientist needs to grasp. The Basics of…