What is natural language generation? Natural Language Generation (NLG) is a subfield of artificial intelligence (AI) and natural language processing (NLP) that focuses on the automatic generation of...
The Natural Language Processing (NLP) Blog
Topic: Neural Networks
Top 8 Loss Functions Made Simple & How To Implement Them In Python
What are loss functions? Loss functions, also known as a cost or objective functions, are critical component in training machine learning models. It quantifies a machine learning model's performance...
How To Implement Cross-lingual Transfer Learning In 5 Different Ways
What is cross-lingual transfer learning? Cross-lingual transfer learning is a machine learning technique that involves transferring knowledge or models from one language to another, typically to...
Understanding Dropout in Neural Network: Enhancing Robustness and Generalization
What is dropout in neural networks? Dropout is a regularization technique used in a neural network to prevent overfitting and enhance model generalization. Overfitting occurs when a neural network...
Graph Neural Network Explained & How To Tutorial In Python With PyTorch
Graph Neural Network (GNN) is revolutionizing the field of machine learning by enabling effective modelling and analysis of structured data. Originally designed for graph-based data, GNNs have found...
Activation Function: Top 9 Most Popular Explained & When To Use Them
What is an activation function? In artificial neural networks, an activation function is a mathematical function that introduces non-linearity to the output of a neuron or a neural network layer. It...
How To Combine Numerical & Text Features: 10 Ways In Machine Learning And Deep Learning
Why Combine Numerical Features And Text Features? Combining numerical and text features in machine learning models has become increasingly important in various applications, particularly natural...
Hyperparameter Tuning In Machine Learning And Deep Learning: Top 6 Ways & How To Tutorial
What is hyperparameter tuning in machine learning? Hyperparameter tuning is critical to machine learning and deep learning model development. Machine learning algorithms typically have specific...
Feedforward Neural Networks Made Simple With Different Types Explained
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...
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...
![Adam Optimizer Explained & How To Use In Python [Keras, PyTorch & TensorFlow]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/03/adam-optimizer.jpg?fit=960%2C540&ssl=1)
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...
![Tutorial TF-IDF vs Word2Vec For Text Classification [How To In Python With And Without CNN]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/02/word2vec-text-classification.jpg?fit=1024%2C576&ssl=1)
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 classification. It is a neural network-based approach that learns distributed...
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...
