How does a feedforward neural network work? What are the different variations? With a detailed explanation of a single-layer feedforward network and a multi-layer feedforward network. What is a...
The Natural Language Processing (NLP) Blog
Topic: Artificial Intelligence
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How To Implement Data Augmentation In Python [Image & Text (NLP)]
Top 7 ways of implementing data augmentation for both images and text. With the top 3 libraries in Python to use for image processing and NLP. What is data augmentation? Data augmentation is a...
Understanding Generative Adversarial Network With A How To Tutorial In TensorFlow And Python
What is a Generative Adversarial Network (GAN)? What are they used for? How do they work? And what different types are there? This article includes a tutorial on how to get started with GANs in...
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Adam Optimizer Explained & How To Use In Python [Keras, PyTorch & TensorFlow]
Explanation, advantages, disadvantages and alternatives of Adam optimizer with implementation examples in Keras, PyTorch & TensorFlow What is the Adam optimizer? The Adam optimizer is a popular...
Backpropagation Made Easy With Examples And How To In Python With Keras
Why is backpropagation important in neural networks? How does it work, how is it calculated, and where is it used? With a Python tutorial in Keras. Introduction to backpropagation in Machine...
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 step-by-step tutorial in Python. What are Restricted Boltzmann Machines? Restricted...
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 than the traditional binary true or false values found in classical logic, it is...
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....
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...
Top 5 Ways To Implement Question-Answering Systems In NLP & A List Of Python Libraries
What is a question-answering System? Question answering (QA) is a field of natural language processing (NLP) and artificial intelligence (AI) that aims to develop systems that can understand and...
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...
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...
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...
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...
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...
