Introduction To NLP Exploratory Data Analysis In today's data-driven world, Natural Language Processing (NLP) has emerged as a transformative field, enabling machines to understand, interpret, and...
The Natural Language Processing (NLP) Blog
Topic: Natural Language Processing
Vector Space Model Made Simple With Examples & Tutorial In Python
What is a Vector Space Model? The Vector Space Model (VSM) is a mathematical framework used in information retrieval and natural language processing (NLP) to represent and analyze textual data. It's...
Practical Guide To Doc2Vec & How To Tutorial In Python
In today's data-driven world, making sense of vast volumes of text data is paramount. Natural Language Processing (NLP) techniques are at the forefront of unlocking the insights hidden within text,...
Information Retrieval Made Simple, Different Types & How They Work
What is information retrieval? Information retrieval (IR) is the process of obtaining information from an extensive repository of data or documents. It involves searching for and retrieving relevant...
Random Forest Classifier – How To Python Tutorial & Practical Guide
What is a Random Forest classifier? A Random Forest classifier is a machine learning algorithm that falls under ensemble learning. It's used for both classification and regression tasks. The "Random...
Latent Semantic Analysis: A Complete Guide With Alternatives & Python Tutorial
What is Latent Semantic Analysis (LSA)? Latent Semantic Analysis (LSA) is used in natural language processing and information retrieval to analyze word relationships in a large text corpus. It is a...
What Is A Large Language Model? Use Cases, Benefits, Limitations & What Does The Future Hold?
What is a large language model? A large language model (LLM) is a type of artificial intelligence (AI) trained on massive text and code datasets. This allows them to learn the patterns and...
![Zero-shot Classification [Top 6 Models, How To Tutorial In Python & Alternatives]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/08/zero-shot-classification.jpg?fit=1200%2C675&ssl=1)
Zero-shot Classification [Top 6 Models, How To Tutorial In Python & Alternatives]
What is zero-shot classification? Zero-shot classification is a machine learning approach in which a model can classify data into multiple classes without any specific training examples for those...
Understanding & Implementing The Continuous Bag-of-Words (CBOW) Model
Introduction to word embeddings Word embeddings have become a cornerstone of Natural Language Processing (NLP), transforming how machines process and understand human language. These vector...
Skip-gram Models Explained & How To Create Embeddings In Word2Vec
What is skip-gram? Skip-gram is a popular algorithm used in natural language processing (NLP), specifically in word embedding techniques. It is a method for learning word representations in a vector...
Top 6 Name Matching Algorithm, How To Scale Your Solution & Tutorial In Python
What is fuzzy name matching? A fuzzy name matching algorithm, or approximate name matching, is a technique used to compare and match names with slight differences, variations, or errors. It is...
Graph Neural Network Explained & How To Tutorial In Python With PyTorch
Graph Neural Network (GNN) is revolutionizing the field of machine learning by enabling effective modelling and analysis of structured data. Originally designed for graph-based data, GNNs have found...
Few-shot Learning Explained & Step-by-step How To Python Tutorial
What is few-shot learning? Few-shot learning is a machine learning technique that aims to train models to learn new tasks or recognise new classes of objects using only a small amount of labelled...
![The History Of Natural Language Processing & Potential Future Breakthroughs [With Infographic Timeline]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/06/history-natural-language-processing.jpg?fit=960%2C540&ssl=1)
The History Of Natural Language Processing & Potential Future Breakthroughs [With Infographic Timeline]
History of natural language processing Natural Language Processing (NLP) has a fascinating history that spans several decades. Let's journey through time to explore the key milestones and...
How To Combine Numerical & Text Features: 10 Ways In Machine Learning And Deep Learning
Why Combine Numerical Features And Text Features? Combining numerical and text features in machine learning models has become increasingly important in various applications, particularly natural...
Open Source Large Language Models (LLM) – Top 10 Most Powerful To Consider In 2024
What are open-source large language models? Open-source large language models, such as GPT-3.5, are advanced AI systems designed to understand and generate human-like text based on the patterns and...
CountVectorizer Tutorial: How To Easily Turn Text Into Features For Any NLP Task
What is CountVectorizer in NLP? CountVectorizer is a text preprocessing technique commonly used in natural language processing (NLP) tasks for converting a collection of text documents into a...
Difference Between Structured And Unstructured Data
Unstructured data has become increasingly prevalent in today's digital age and differs from the more traditional structured data. With the exponential growth of information on the internet, the vast...
