Introduction to document clustering and its importance Grouping similar documents together in Python based on their content is called document clustering, also known as text clustering. This...
The Natural Language Processing (NLP) Blog
Machine Learning – Deep Learning – Data Science
Local Sensitive Hashing (LSH)— Complete Guide & How To Get Started In Python
What is local sensitive hashing? A technique for performing a rough nearest neighbour search in high-dimensional spaces is called local sensitive hashing (LSH). It operates by mapping...
How To Use One Hot Encoding In Python With 3 Tutorials
Categorical variables are variables that can take on one of a limited number of values. These variables are commonly found in datasets and can't be used directly in machine learning models as most...
Top 6 Most Useful Attention Mechanism In NLP Explained And When To Use Them
Numerous tasks in natural language processing (NLP) depend heavily on an attention mechanism. When the data is being processed, they allow the model to focus on only certain input elements, such as...
How To Use LSTM In NLP Tasks With A Text Classification Example Using Keras
Long Short-Term Memory (LSTM) is a powerful natural language processing (NLP) technique. This powerful algorithm can learn and understand sequential data, making it ideal for analyzing text and...
CNN In NLP: Top 5 Types & How To Tutorial For Text Classification With TensorFlow
Convolutional Neural Networks (CNN) are a type of deep learning model that is particularly well-suited for tasks that involve working with structured data, such as images, audio, or text in NLP....
Top 5 Best RNN In NLP Simplified & How To Tutorial In Python With Keras
Best RNN For NLP: Elman RNNs, Long short-term memory (LSTM) networks, Gated recurrent units (GRUs), Bi-directional RNNs and Transformer networks What is an RNN? A recurrent neural network (RNN) is...
Encoder Decoder Neural Network Simplified, Explained & State Of The Art
Encoder, decoder and encoder-decoder transformers are a type of neural network currently at the bleeding edge in NLP. This article explains the difference between these architectures and what they...
![Hidden Markov Model (HMM) For NLP Made Easy [How To In Python]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/01/hmm-nlp.jpg?fit=1024%2C576&ssl=1)
Hidden Markov Model (HMM) For NLP Made Easy [How To In Python]
What is a Hidden Markov Model in NLP? A time series of observations, such as a Hidden Markov Model (HMM), can be represented statistically as a probabilistic model. Natural language processing (NLP)...
Most Popular Deep Learning Algorithms For Natural Language Processing (NLP)
What is deep learning for natural language processing? Deep learning is a part of machine learning based on how the brain works, especially the neural networks that make up the brain. It requires...
What Is Neural Machine Translation? & 4 Easy Python Tools
Neural machine translation (NMT) is a state-of-the-art technique for translation. Our previous article on translating text in Python covered the two most common ways of getting started with...
NLP Transfer Learning Made Easy, Top 5 Models & How To Use Them
Transfer learning is explained, and the advantages and disadvantages are summed up. Types of transfer learning in NLP are summed up, and a list of the top models commonly used for transfer learning...
MinHash — How To Deal With Finding Similarity At Scale With Python Code To Get Started
What is MinHash? MinHash is a technique for estimating the similarity between two sets. It was first introduced in information retrieval to evaluate the similarity between documents quickly. The...
SimHash — The Ultimate Guide And How To Get Started Guide In Python
What is SimHash? Simhash is a technique for generating a fixed-length "fingerprint" or "hash" of a variable-length input, such as a document or a piece of text. It is similar to a hash function and...
![How To Implement Fuzzy String Matching [4 Ways In Python]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/01/fuzzy-logic-hot-cold.jpg?fit=1024%2C1024&ssl=1)
How To Implement Fuzzy String Matching [4 Ways In Python]
This article discusses one of the most valuable tools when analysing textual data in natural language processing — fuzzy string matching. We first discuss what it is, its typical applications and...
![How To Implement Abstractive Text Summarization In Python [2 Ways]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2022/12/summarization.jpg?fit=1024%2C576&ssl=1)
How To Implement Abstractive Text Summarization In Python [2 Ways]
Abstractive text summarization is a valuable tool in Python when working with large documents, or you quickly want to summarize data. In this article, we discuss applications of abstractive text...
Top 15 Most Popular Machine Learning And Deep Learning Algorithms For NLP
This list covers the top 7 machine learning algorithms and 8 deep learning algorithms used for NLP. If you are new to using machine learning algorithms for NLP, we suggest starting with the first...
Reinforcement Learning In NLP Made Simple & 5 Relevant Tools To Get Started
This article covers reinforcement learning and its application in natural language processing (NLP). It also covered the latest developments in the field, a discussion on whether you should start...
