Comparison of Sigmoid, Tanh and ReLU Activation Functions
Introduction In Artificial Neural network (ANN), activation functions are the most informative ingredient of Deep Learning which is fundamentally used for to determine the output of the deep learning models. In…
Understand Types of Environments in Artificial Intelligence
The Environment is the surrounding world around the agent which is not part of the agent itself. It’s important to understand the nature of the environment when solving a problem…
8 Important Evaluation Metrics for Classification Models
This post explains important evaluation metrics to check while measuring the performance of a classification model. These are Accuracy, Precision, Recall, Sensitivity, Specificity, False Positive Rate, False Negative Rate, and…
Understand Confusion Matrix Using Real-life Classification Example
First I’d like to explain what is the use of a confusion matrix. Classification Problems are solved using Supervised Machine learning algorithms. In these problems, our goal is to categories…
Explain Echelon Form of a Matrix
Echelon Form of a matrix is used to solve a linear equation by converting a complex matrix to a simple matrix. A matrix is in an Echelon Form if it…
Working of Bagging and Boosting in Ensemble Learning
Bagging and Boosting both are Ensemble Learning techniques. Ensemble Methods are an important addition to Data Scientists toolbox. Here, weak learners combined together to become strong learners. And offers better…
What is the difference between Variance and Bias in Machine Learning?
From the perspective of Supervised Machine Learning, we know all models have errors. We need to minimize the error so as to make the model useful. For this, we need…
Decision Tree vs Random Forest in Machine Learning : Which One Should You Actually Use?
If you've gotten far enough into machine learning to be comparing decision trees and random forests, you already know the short answer: random forest almost always wins on accuracy, decision…
Decision Tree in Machine Learning with Example
Decision Tree algorithm belongs to the Supervised Machine Learning. It can use to solve Regression and Classification problems. It creates a training model which predicts the value of target variables…
Solving Regression Problems Using Neural Network
This tutorial explains solving regression problems using a neural network approach instead of using Supervised Machine Learning Algorithm. You'll be able to solve simple regression problems at the end of…
