Introduction Every organisation today is flooded with documents — contracts, invoices, reports, customer feedback, medical records, research papers, and more. These documents hold critical...
![Machine Learning For Documents [How It Works & 15 Popular Tools]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2025/10/ml-pipeline-for-documents.jpg?fit=1200%2C675&ssl=1)
The Natural Language Processing (NLP) Blog
Topic: Natural Language Processing
![Low-Resource NLP Made Simple [Challenges, Strategies, Tools & Libraries]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2025/09/stratagies-low-resource-nlp.jpg?fit=1200%2C675&ssl=1)
Low-Resource NLP Made Simple [Challenges, Strategies, Tools & Libraries]
Introduction Natural Language Processing (NLP) powers many of the technologies we use every day—search engines, chatbots, translation tools, and voice assistants. However, behind the scenes, most of...
Top 14 Python Natural Language Processing (NLP) Libraries With How To Tutorials
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...
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...
NLP And Edge Computing: How It Works & Top 7 Technologies for Offline Computing
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...
![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...
How To Process Text In Python With Pandas Made Simple
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...
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....
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...
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...
![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...
BLEU Score In NLP: What Is It & How To Implement In Python
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...
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...
