What is a Gated Recurrent Unit? A Gated Recurrent Unit (GRU) is a Recurrent Neural Network (RNN) architecture type. It is similar to a Long Short-Term Memory (LSTM) network but has fewer parameters...
The Natural Language Processing (NLP) Blog
Topic: Machine Learning
![How To Implement Transformers For Natural Language Processing (NLP) [4 Python Tutorials]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/01/transformers.jpg?fit=1024%2C576&ssl=1)
How To Implement Transformers For Natural Language Processing (NLP) [4 Python Tutorials]
Transformers Implementations in TensorFlow, PyTorch, Hugging Face and OpenAI's GPT-3 What are transformers in natural language processing? Natural language processing (NLP) is a field of artificial...
The Curse Of Variability In Machine Learning And How To Overcome It
What is the curse of variability? The curse of variability refers to the idea that as the variability of a dataset increases, the difficulty of finding a good model that can accurately predict...
Siamese Network In Natural Language Processing (NLP) Made Simple & How To Tutorial In Python
What is a Siamese network? It is also commonly known as one or few-shot learning. They are popular because less labelled data is required to train them. Siamese networks are often used to figure out...
Top 6 Most Popular Text Clustering Algorithms And How They Work Explained
What exactly is text clustering? The process of grouping a collection of texts into clusters based on how similar their content is is known as text clustering. Text clustering combines related...
Tutorial On How To Implement Document Clustering In Python With K-means
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...
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...
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...
![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...
![Text Classification: How To In Python [Best 2 Ways Machine Learning & Deep Learning]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2022/12/random-forest.jpg?fit=960%2C540&ssl=1)
Text Classification: How To In Python [Best 2 Ways Machine Learning & Deep Learning]
Text classification is an important natural language processing (NLP) technique that allows us to turn unstructured data into structured data; many different algorithms allow you to do this, and so...
Top 7 Ways To Implement Document & Text Similarity In Python: NLTK, Scikit-learn, BERT, RoBERTa, FastText and PyTorch
Text similarity is a really useful natural language processing (NLP) tool. It allows you to find similar pieces of text and has many real-world use cases. This article discusses text similarity, its...
