What Are Embedding Models? At their core, embedding models are tools that convert complex data—such as words, sentences, images, or even audio—into numerical representations. More specifically, they...

What Are Embedding Models? At their core, embedding models are tools that convert complex data—such as words, sentences, images, or even audio—into numerical representations. More specifically, they...
What Are Vector Embeddings? Imagine trying to explain to a computer that the words "cat" and "dog" are more similar to each other than to "car". Computers don't inherently understand language,...
Introduction Imagine trying to understand what someone said over a noisy phone call or deciphering a DNA sequence from partial biological data. In both cases, you're trying to uncover a hidden...
What is Structured Prediction? In traditional machine learning tasks like classification or regression a model predicts a single label or value for each input. For example, an image classifier might...
In the age of digital transformation, Natural Language Processing (NLP) has emerged as a cornerstone of intelligent applications. From chatbots and voice assistants to real-time translation and...
What is Anomaly Detection in LLMs? Anomaly detection in the context of Large Language Models (LLMs) involves identifying outputs, patterns, or behaviours that deviate significantly from what is...
What is Text Annotation? Text annotation is the process of labelling or tagging text data with specific information, making it more understandable and usable for machine learning models or other...
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...
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....
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...
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...
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...
Introduction to Perplexity in NLP In the rapidly evolving field of Natural Language Processing (NLP), evaluating the effectiveness of language models is crucial. One of the key metrics used for this...
What is the BLEU Score in NLP? BLEU, Bilingual Evaluation Understudy, is a metric used to evaluate the quality of machine-generated text in NLP, most commonly in machine translation. Kishore...
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...
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...
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 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...
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