Text classification is a fundamental problem in natural language processing (NLP) that involves categorising text data...
The Natural Language Processing (NLP) Blog
Machine Learning – Deep Learning – Data Science
Machine Learning
Restricted Boltzmann Machines Explained & How To Tutorial In Python
How are RBMs used in deep learning? Examples, applications and how it is used in collaborative filtering. With a...
SMOTE Oversampling & Tutorial On How To Implement In Python And R
How does the algorithm work? What are the disadvantages and alternatives? And how do we use it in machine learning?...
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Tutorial TF-IDF vs Word2Vec For Text Classification [How To In Python With And Without CNN]
Word2Vec for text classification Word2Vec is a popular algorithm used for natural language processing and text...
Fuzzy Logic Made Easy — Its Application In AI, Machine Learning & Natural Language Processing (NLP)
What is fuzzy logic? Fuzzy logic is a mathematical approach to reasoning about uncertain or vague information. Rather...
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...
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....
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...
Self-attention Made Easy And 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...
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...
Top 4 Best Ways To Implement Transformers For Natural Language Processing (NLP)
Transformers Implementations in TensorFlow, PyTorch, Hugging Face and OpenAI's GPT-3 What are transformers in natural...
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...
How To Implement A Siamese Network In NLP — Made Easy With Python
What is a Siamese network? It is also commonly known as one or a few-shot learning. They are popular because less...
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...
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...
Local Sensitive Hashing — 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...
Top 3 Ways To Get Started With One Hot Encoding In Python & Understand When To Use It
Categorical variables are variables that can take on one of a limited number of values. These variables are commonly...
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...
