What is fuzzy logic? Fuzzy logic is a mathematical approach to reasoning about uncertain or vague information. Rather than the traditional binary true or false values found in classical logic, it is...
The Natural Language Processing (NLP) Blog
Topic: Machine Learning
Deep Belief Network — Explanation, Application & How To Get Started In TensorFlow
How does the Deep Belief Network algorithm work? Common applications. Is it a supervised or unsupervised learning method? And how do they compare to CNNs? And how to create an implementation in...
The Vanishing Gradient Problem, How To Detect & Overcome It
When does it occur? How can you recognise it? And how to adapt your network to avoid the vanishing gradient problem. What is the vanishing gradient problem? The vanishing gradient problem is a...
Understanding Elman RNN — Uniqueness & How To Implement In Python With PyTorch
What is the Elman neural network? Elman Neural Network is a recurrent neural network (RNN) designed to capture and store contextual information in a hidden layer. Jeff Elman introduced it in 1990....
Self-attention Made Easy & How To Implement It In PyTorch
Self-attention is the reason transformers are so successful at many NLP tasks. Learn how they work, the different types, and how to implement them with PyTorch in Python. What is self-attention in...
Gated Recurrent Unit Explained & How They Compare LSTM, RNN & CNN
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...
![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...
