Introduction Text data is everywhere—from social media posts and customer reviews to emails and product descriptions. For data scientists and analysts, working with this unstructured form of data...

# The Natural Language Processing (NLP) Blog

## Handling Missing Data In Machine Learning: Top 8 Techniques & How To Tutorial In Python

What is Missing Data in Machine Learning? In machine learning, the quality and completeness of data are often just as important as the algorithms and models we choose. Though common in real-world...

## Predictive Analytics Made Simple & How To Python Tutorial

What is Predictive Analytics? Predictive analytics uses historical data, statistical algorithms, and machine learning techniques to identify patterns and forecast future outcomes. At its core, it...

## Linear Regression In Machine Learning Made Simple & How To Python Tutorial

What is Linear Regression in Machine Learning? Linear regression is one of the fundamental techniques in machine learning and statistics used to understand the relationship between one or more...

## Out-of-Vocabulary (OOV) Words Explained & How To Handle Them In NLP Tasks

What are Out-of-Vocabulary (OOV) Words? In Natural Language Processing (NLP), Out-of-Vocabulary (OOV) words refer to any words a machine learning model has not encountered during its training phase....

## Text Representation: A Simple Explanation Of Complex Techniques

What is Text Representation? Text representation refers to how text data is structured and encoded so that machines can process and understand it. Human language is inherently complex, filled with...

## Wavelet Transform Made Simple [Foundation, Applications, Advantages]

Introduction to Wavelet Transform What is Signal Processing? Signal processing is critical in various fields, from telecommunications to medical diagnostics and multimedia applications. It involves...

## Precision And Recall In Machine Learning Made Simple: How To Handle The Trade-off

What is Precision and Recall? When evaluating a classification model's performance, it's crucial to understand its effectiveness at making predictions. Two essential metrics that help assess this...

## Confusion Matrix: A Beginners Guide & How To Tutorial In Python

What is a Confusion Matrix? A confusion matrix is a fundamental tool used in machine learning and statistics to evaluate the performance of a classification model. At its core, a tablet lets you...

## Understand Ordinary Least Squares: How To Beginner’s Guide [Tutorials In Python, R & Excell]

What is Ordinary Least Squares (OLS)? Ordinary Least Squares (OLS) is a fundamental technique in statistics and econometrics used to estimate the parameters of a linear regression model. In simple...

## METEOR Metric In NLP: How It Works & How To Tutorial In Python

What is the METEOR Score? The METEOR score, which stands for Metric for Evaluation of Translation with Explicit ORdering, is a metric designed to evaluate the text quality generated by machine...

## ROUGE Metric In NLP: Complete Guide & How To Tutorial In Python

What is the ROUGE Metric? ROUGE, which stands for Recall-Oriented Understudy for Gisting Evaluation, is a set of metrics used to evaluate the quality of summaries and translations generated by...

## Normalised Discounted Cumulative Gain (NDCG): Complete How To Guide

What is Normalised Discounted Cumulative Gain (NDCG)? Normalised Discounted Cumulative Gain (NDCG) is a popular evaluation metric used to measure the effectiveness of search engines, recommendation...

## Mean Reciprocal Rank (MRR): How It Works [A Complete Guide]

What is Mean Reciprocal Rank (MRR)? Mean Reciprocal Rank (MRR) is a metric used to evaluate the effectiveness of information retrieval systems, such as search engines and recommendation systems. It...

## Ethical AI Explained: Key Issues & Practical How To Implement Guide

What is Ethical AI? Ethical AI involves developing and deploying artificial intelligence systems prioritising fairness, transparency, accountability, and respect for user privacy and autonomy. It...

## Understanding Ranking Algorithms: A Comprehensive Guide & How To Implement

What are Ranking Algorithms? Ranking algorithms are computational processes used to order items, such as web pages, products, or multimedia content, based on their relevance or importance to a given...

## Ultimate Guide To Data Structure Hashing With How To Tutorial In Python

What is Hashing? Hashing is used in computer science as a data structure to store and retrieve data efficiently. At its core, hashing involves taking an input (or "key") and running it through a...

## ROC And AUC Curves In Machine Learning Made Simple & How To Tutorial In Python

What are ROC and AUC Curves in Machine Learning? The ROC Curve The ROC (Receiver Operating Characteristic) curve is a graphical representation used to evaluate the performance of binary...