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...

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...
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...
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,...
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...
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...
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...
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...
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...
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...
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...
What is Cosine Annealing? In the vast landscape of optimisation algorithms lies a hidden gem that has been gaining increasing attention in recent years: cosine annealing. Optimisation algorithms are...
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...
What is Online Machine Learning? Online machine learning, also known as incremental or streaming learning, is a type of machine learning in which models are updated continuously as new data becomes...
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...
What are Classification Metrics in Machine Learning? In machine learning, classification tasks are omnipresent. From spam detection in emails to medical diagnosis and sentiment analysis in social...
What are Co-occurrence Matrices? Co-occurrence matrices serve as a fundamental tool across various disciplines, unveiling intricate statistical relationships hidden within data. Whether in natural...
What is Query Understanding? Understanding user queries lies at the heart of efficient communication between humans and machines in the vast digital information and interaction landscape. Query...
What is Distributional Semantics? Understanding the meaning of words has always been a fundamental challenge in natural language processing (NLP). How do we decipher the intricate nuances of...
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