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...
The Natural Language Processing (NLP) Blog
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....
Multi-Task Learning Made Simple & Popular Approaches Explained
What is Multi-Task Learning? Multi-TaskMulti-task learning (MTL) is a machine learning approach in which a single model is trained to solve multiple tasks simultaneously rather than learning each...
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...
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...
BERTScore – A Powerful NLP Evaluation Metric Explained & How To Tutorial In Python
What is BERTScore? BERTScore is an innovative evaluation metric in natural language processing (NLP) that leverages the power of BERT (Bidirectional Encoder Representations from Transformers) to...
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...
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...
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...
Bias Mitigation in Machine Learning [Practical How-To Guide & 12 Strategies]
In machine learning (ML), bias is not just a technical concern—it's a pressing ethical issue with profound implications. As AI systems become increasingly integrated into our daily lives, from...
Support Vector Machines (SVM) In Machine Learning Made Simple & How To Tutorial
What are Support Vector Machines? Machine learning algorithms transform raw data into actionable insights. Among these algorithms, Support Vector Machines (SVMs) stand out as a core algorithm for...
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...