What is the Exploding Gradient Problem? Neural networks optimize their parameters using gradient-based optimization algorithms like gradient descent. Gradients represent the slope of the loss...
The Natural Language Processing (NLP) Blog
Machine Learning – Deep Learning – Data Science
Reinforcement Learning: Q-learning & Deep Q-Learning Made Simple
What is Q-learning in Machine Learning? In machine learning, Q-learning is a foundational reinforcement learning technique for decision-making in uncertain environments. Unlike supervised learning,...
Generative Artificial Intelligence (AI) Made Simple [Complete Guide With Models & Examples]
What is Generative Artificial Intelligence (AI)? Generative artificial intelligence (GAI) is a type of AI that can create new and original content, such as text, music, images, and videos. It is...
How To Guide To Chat-GPT, GPT-3 & GPT-4 Prompt Engineering [10 Types]
What is GPT prompt engineering? GPT prompt engineering is the process of crafting prompts to guide the behaviour of GPT language models, such as Chat-GPT, GPT-3, GPT-3.5-Turbo, and GPT-4. It...
How to manage Large Language Models (LLM) — Orchestration Made Simple [5 Frameworks]
What is LLM Orchestration? LLM orchestration is the process of managing and controlling large language models (LLMs) in a way that optimizes their performance and effectiveness. This includes tasks...
Generative Models Made Simple: Understand How They Work & Different Types
What are Generative Models? In the ever-evolving landscape of artificial intelligence, generative models have emerged as one of AI technology's most captivating and creative facets. These models are...
Retrieval-Augmented Generation (RAG) Made Simple & 2 How To Tutorials
What is Retrieval-Augmented Generation (RAG)? Retrieval-augmented generation (RAG) is a natural language processing (NLP) technique that combines information retrieval capabilities with text...
Pre-Trained Models Complete Guide [How To & 21 Top Models In PyTorch, TensorFlow & HuggingFace]
Understanding Pre-Trained Models Pre-trained models have become a game-changer in artificial intelligence and machine learning. They offer a shortcut to developing highly capable models for various...
Teacher Forcing In Recurrent Neural Networks (RNNs): An Advanced Concept Made Simple
What is teacher forcing? Teacher forcing is a training technique commonly used in machine learning, particularly in sequence-to-sequence models like Recurrent Neural Networks (RNNs) and...
Mode Collapse In GANs Explained, How To Detect It & Practical Solutions
What is mode collapse in Generative Adversarial Networks (GANs)? Mode collapse is a common issue in generative models, particularly in the context of generative adversarial networks (GANs) and some...
Natural Language Understanding — What Is It & How To Go Beyond NLP
What is Natural Language Understanding? Natural Language Understanding (NLU) is the cornerstone of modern artificial intelligence that empowers machines to grasp the complexities of human language....
Continual Learning Made Simple, How To Get Started & Top 4 Models
The need for continual learning In the ever-evolving landscape of machine learning and artificial intelligence, the ability to adapt and learn continuously (continual learning) has become...
Natural Language Generation Explained & 2 How To Tutorials In Python
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...
Understanding Meta-Learning — How To Be More Effective With Less Data
What is meta-learning? Meta-learning, or learning to learn, is a machine learning approach that focuses on improving the learning process rather than just learning a specific task or problem....
What Is A Large Language Model? Use Cases, Benefits, Limitations & What Does The Future Hold?
What is a large language model? A large language model (LLM) is a type of artificial intelligence (AI) trained on massive text and code datasets. This allows them to learn the patterns and...
Understanding & Implementing The Continuous Bag-of-Words (CBOW) Model
Introduction to word embeddings Word embeddings have become a cornerstone of Natural Language Processing (NLP), transforming how machines process and understand human language. These vector...
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...
Few-shot Learning Explained & Step-by-step How To Python Tutorial
What is few-shot learning? Few-shot learning is a machine learning technique that aims to train models to learn new tasks or recognise new classes of objects using only a small amount of labelled...