Logarithmic loss (or cross-entropy) measures the performance of a classification model where the prediction input is a probability value between 0 and 1. The goal of our machine learning models is to minimize this value. It is also heavily used Read more…
For binary classification problems, a good way to measure the performance of a model is by finding out AUC (Area Under The Curve) of ROC (Receiver Operating Characteristics). What is a ROC curve? It is a plot of True Positive Read more…
Confusion Matrix Confusion Matrix is a group or matrix of metrics in supervised learning scenarios which determine how good a model is in predictions. Lets consider a binary classifier with results 1 or 0. A confusion matrix here will be Read more…
Hypothesis Testing Hypothesis tests, also called significance tests, are ubiquitous in the traditional statistical analysis of published research. Their purpose is to help you learn whether random chance might be responsible for an observed effect. KEY TERMS Null hypothesis The Read more…
Welcome to part 1 of writing python like a pro. This series is definitely part of the advanced python series. It assumes you already know python and are definitely comfortable with it. However, you are a person who wants to Read more…
This is part 2 of Introduction to Dimensionality Reduction. In this blog post, we would several different mathematical prerequisites that one must know before trying to understand machine learning. Mean Vector The sample mean is a vector each of whose Read more…
In this series, we would focus on some of the language-agnostic parts which can be used to improve your ability to write cleaner code in any language. So let’s dive right into the SOLID concepts of object-oriented design. S.O.L.I.D is an Read more…
Introduction to Dimensionality Reduction There are several ways we can define Dimensionality Reduction. One way to define it is: Dimensionality Reduction refers to the process of converting a set of data having vast dimensions into data with lesser dimensions ensuring Read more…
Before applying any dimensionality reduction technique sometimes it is important to preprocess the data. There are several ways which we can use for preprocessing data. In this post, we will explore one of the common ways to do data preprocessing Read more…
Writing clean code is more of an art rather than a science. So What really makes code cleaner?. In this series called Clean Code Concepts, we investigate some of the ways to write code in a clean way. There are Read more…