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...
The Natural Language Processing (NLP) Blog
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...
Naive Bayes Classification Made Simple & How To Tutorial In Python
What is Naive Bayes? Naive Bayes classifiers are a group of supervised learning algorithms based on applying Bayes' Theorem with a strong (naive) assumption that every feature in the dataset is...
How To Implement Anomaly Detection With One-Class SVM In Python
What is One-Class SVM? One-class SVM (Support Vector Machine) is a specialised form of the standard SVM tailored for unsupervised learning tasks, particularly anomaly detection. Unlike traditional...
Decision Trees In ML Complete Guide [How To Tutorial, Examples, 5 Types & Alternatives]
What are Decision Trees? Decision trees are versatile and intuitive machine learning models for classification and regression tasks. It represents decisions and their possible consequences,...
Isolation Forest For Anomaly Detection Made Easy & How To Tutorial
What is an Isolation Forest? Isolation Forest, often abbreviated as iForest, is a powerful and efficient algorithm designed explicitly for anomaly detection. Introduced by Fei Tony Liu, Kai Ming...
Batch Gradient Descent In Machine Learning Made Simple & How To Tutorial In Python
What is Batch Gradient Descent? Batch gradient descent is a fundamental optimization algorithm in machine learning and numerical optimisation tasks. It is a variation of the gradient descent...
Full-Text Search Explained, How To Implement & 6 Powerful Tools
What is Full-Text Search? Full-text search is a technique for efficiently and accurately retrieving textual data from large datasets. Unlike traditional search methods that rely on simple string...
Support Vector Regression (SVR) Simplified & How To Tutorial In Python
What is Support Vector Regression (SVR)? Support Vector Regression (SVR) is a machine learning technique for regression tasks. It extends the principles of Support Vector Machines (SVM) from...
Weight Decay In Machine Learning And Deep Learning Explained & How To Tutorial
What is Weight Decay in Machine Learning? Weight decay is a pivotal technique in machine learning, serving as a cornerstone for model regularisation. As algorithms become increasingly complex and...
Collaborative Filtering In Machine Learning Made Simple [6 Different Approaches]
What is Collaborative Filtering? In today's digital era, where we are inundated with overwhelming information and choices, recommendation systems have become indispensable. From suggesting movies to...
Data Drift In Machine Learning Explained: How To Detect & Mitigate It
What is Data Drift Machine Learning? In machine learning, the accuracy and effectiveness of models heavily rely on the quality and consistency of the data on which they are trained. However, in...