What is local sensitive hashing? A technique for performing a rough nearest neighbour search in high-dimensional...
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How To Get Started With One Hot Encoding
Categorical variables are variables that can take on one of a limited number of values. These variables are commonly...
Different Attention Mechanism In NLP Made Easy
Numerous tasks in natural language processing (NLP) depend heavily on an attention mechanism. When the data is being...
Why And 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...
Understanding How To Structure CNN In NLP
Different types of CNNs explained and when to use them Convolutional Neural Networks (CNN) are a type of deep learning...
Advanced NLP Made Easy – How To Get Started With RNN
Elman RNNs, Long short-term memory (LSTM) networks, Gated recurrent units (GRUs), Bi-directional RNNs and Transformer...
Encoder Decoder Neural Network Simplified — When To Use Them
Encoder, decoder and encoder-decoder transformers are a type of neural network currently at the bleeding edge in NLP....
Hidden Markov Model (HMM) For NLP Made Easy
What is a Hidden Markov Model in NLP? A time series of observations, such as a Hidden Markov Model (HMM), can be...
Most Popular Deep Learning For Natural Language Processing
What is deep learning for natural language processing? Deep learning is a part of machine learning based on how the...
Neural Machine Translation – A Powerful Tool And How It Works
Neural machine translation (NMT) is a state-of-the-art technique for translation. Our previous article on translating...
NLP Transfer Learning — The Easy Way To Utilise Deep Learning
What is transfer learning in NLP? Transfer learning is a machine learning method in which a model trained on one...
MinHash — How To Deal With Finding Similarity At Scale
What is MinHash? MinHash is a technique for estimating the similarity between two sets. It was first introduced in...