Introduction Imbalanced data is a common problem with data that has to be used for machine learning classification. Class differences can be found in many different areas including Medical Diagnosis, Spam filtering, and Fraud Detection, The main problem with Imbalanced Data is that most of the Machine Learning Algorithms work best…

Introduction Linear regression is employed to approximate the (linear) relationship between an endless response variable and a group of predictor variables. However, when the response variable is binary (i.e., Yes/No), linear regression isn’t appropriate. Fortunately, analysts can turn to an analogous method of logistic regression, which is similar to linear regression…

Introduction In today’s day and age data is a very essential resource as well as a commodity for organizations that allows them to find new ways to grow, find causes of problems and formulate solutions. Every click or post or search we do is data for these organizations as the cost…

What is SDLC? Software Development Life Cycle or SDLC is a framework used in the software industry to design, develop and test high-quality software. …

What is a Data Outlier? An outlier is a data point that is distinct from other similar points. It may be due to variability in the measurement or may indicate experimental errors/ If, possible, outliers should be excluded from the dataset. However, detecting these instances might be difficult, and is not always possible. Machine learning…

This Tutorial is part one of a series of tutorials on subprocesses that are done while working on a Data Science Project. I will try to answer all the questions that come into the mind of a data science rookie covering all the why, how, and what along the way…

Introduction

What is Clustering?

The term linear regression generally refers to predicting a real number. However, it can also be used for classification (predicting a category or a class). The term linear in the name linear regression refers to the fact that the method models data with a linear combination of the explanatory variables. Types of Linear Regression …