Introduction Language is at the heart of human communication—and in today's digital world, making sense of language at scale is more important than ever. From powering chatbots and voice assistants...
The Natural Language Processing (NLP) Blog
Topic: Natural Language Understanding
Embedding Models Explained, How To Use Them & 10 Tools/Frameworks
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...
Vector Embeddings Made Simple & How To Tutorial In Python
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,...
![Viterbi Algorithm Made Simple [How To & Worked-Out Examples]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2025/06/viterbi-algorithm-example.jpg?fit=330%2C348&ssl=1)
Viterbi Algorithm Made Simple [How To & Worked-Out Examples]
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...
Structured Prediction In Machine Learning: What Is It & How To Do It
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...
![Anomaly Detection In LLM Responses [How To Monitor & Mitigate]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/11/types-of-anomalies-llms.jpg?fit=1200%2C675&ssl=1)
Anomaly Detection In LLM Responses [How To Monitor & Mitigate]
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...
Text Annotation Made Simple And 7 Popular Tools
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...
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...
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...
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...
![Perplexity In NLP: Understand How To Evaluate LLMs [Practical Guide]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/08/perplexity-in-nlp-explained.jpg?fit=1920%2C1080&ssl=1)
Perplexity In NLP: Understand How To Evaluate LLMs [Practical Guide]
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...
![Mean Reciprocal Rank (MRR): How It Works [A Complete Guide]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/08/mean-reciprocal-rank-mrr.jpg?fit=1200%2C675&ssl=1){kind=icon}
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...
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...
![Query Understanding In NLP Simplified & How It Works [5 Techniques]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/04/query-understanding.jpg?fit=1200%2C675&ssl=1)
Query Understanding In NLP Simplified & How It Works [5 Techniques]
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...
Distributional Semantics Simplified & 7 Techniques [How To Understand Language]
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...
![The BERT Algorithm (NLP) Made Simple [Understand How Large Language Models (LLMs) Work]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2024/02/self-attention-example-1.jpg?fit=1200%2C675&ssl=1)
The BERT Algorithm (NLP) Made Simple [Understand How Large Language Models (LLMs) Work]
What is BERT in the context of NLP? In Natural Language Processing (NLP), the quest for models genuinely understanding and generating human language has been a longstanding challenge. One...
