Simple Guide to the confusion matrix

A confusion matrix is a table that is often used to describe the performance of the classification model (or "classifier") on a set of test data for which the true values are known. The confusion matrix itself is relatively simple to understand, but the related terminology can be confusing. Confusion matrix A classification problem can be evaluated … Continue reading Simple Guide to the confusion matrix

Overfitting in Machine Learning

In this guide, we’ll walk you through exactly what overfitting means, how to spot it in your models, and what to do if your model is overfitting. By the end, you’ll know how to deal with this tricky problem once and for all. Table of Contents Examples of Overfitting Signal vs. Noise Goodness of fit … Continue reading Overfitting in Machine Learning

Data Imputation Techniques in Machine Learning

Have you come across the problem of handling missing data/values for respective features in machine learning (ML) models during prediction time? This is different from handling missing data for features during training/testing phase of ML models. Data scientists are expected to come up with an appropriate strategy to handle missing data during, both, model training/testing phase and also model prediction time … Continue reading Data Imputation Techniques in Machine Learning

Python consumes a lot of memory or how to reduce the size of objects?

A memory problem may arise when a large number of objects are active in RAM during the execution of a program, especially if there are restrictions on the total amount of available memory. Below is an overview of some methods of reducing the size of objects, which can significantly reduce the amount of RAM needed … Continue reading Python consumes a lot of memory or how to reduce the size of objects?

An Introduction to Neural Networks

Here’s something that might surprise you: neural networks aren’t that complicated! The term “neural network” gets used as a buzzword a lot, but in reality they’re often much simpler than people imagine. This post is intended for complete beginners and assumes ZERO prior knowledge of machine learning. We’ll understand how neural networks work while implementing … Continue reading An Introduction to Neural Networks

Role Of Data Analysis In Business

In this blog post, we discuss the roles of data analysis in business, discuss how data are used in evaluating business performance, introduce some fundamental issues of statistics and measurement and a support tool for data analysis and decision making. DATA IN THE BUSINESS ENVIRONMENT Data are used in virtually every major function in business, … Continue reading Role Of Data Analysis In Business

Difference between classification and association algorithms

The term data mining refers loosely to finding relevant information or discovering knowledge from a large volumes of data. Like knowledge discovery in artificial intelligence, data mining attempts to discover statistical rules and patterns automatically from data. Knowledge discovered from a database can be represented by a set of rules. The following is an example … Continue reading Difference between classification and association algorithms

Quantum Machine Learning

A curated list of quantum machine learning algorithms, study materials, libraries, and software (by language). Why Quantum Machine Learning? Machine Learning(ML) is just a term in recent days but the work effort start from 18th century. What is Machine Learning?, In Simple word the answer is making the computer or application to learn themselves . … Continue reading Quantum Machine Learning