What is Retrieval-Augmented Generation (RAG)? Retrieval-augmented generation (RAG) is a natural language processing (NLP) technique that combines information retrieval capabilities with text...
The Natural Language Processing (NLP) Blog
Topic: Artificial Intelligence
![Pre-Trained Models Complete Guide [How To & 21 Top Models In PyTorch, TensorFlow & HuggingFace]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/10/pre-trained-models.jpg?fit=960%2C540&ssl=1)
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...
![The History Of Natural Language Processing & Potential Future Breakthroughs [With Infographic Timeline]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/06/history-natural-language-processing.jpg?fit=960%2C540&ssl=1)
The History Of Natural Language Processing & Potential Future Breakthroughs [With Infographic Timeline]
History of natural language processing Natural Language Processing (NLP) has a fascinating history that spans several decades. Let's journey through time to explore the key milestones and...
Open Source Large Language Models (LLM) – Top 10 Most Powerful To Consider In 2024
What are open-source large language models? Open-source large language models, such as GPT-3.5, are advanced AI systems designed to understand and generate human-like text based on the patterns and...
Fine-tuning GPT-3: How To Tutorial In Python With Hugging Face
What is GPT-3? GPT-3 (Generative Pre-trained Transformer 3) is a state-of-the-art language model developed by OpenAI, a leading artificial intelligence research organization. GPT-3 is a deep neural...
Top 20 Most Powerful Large Language Models For NLP Tasks & Transfer Learning In 2024
Natural Language Processing (NLP) has become an essential area of research and development in Artificial Intelligence (AI) in recent years. NLP models have been designed to help computers...
How To Apply Transfer Learning To Large Language Models (LLMs) — Detailed Explanation & Tutorial To Fine Tune A GPT-3 model
What is transfer learning for large language models (LLMs)? Their Advantages, disadvantages, different models available and applications in various natural language processing (NLP) tasks. Followed...
Top 8 Most Useful Anomaly Detection Algorithms For Time Series And Common Libraries For Implementation
How does anomaly detection in time series work? What different algorithms are commonly used? How do they work, and what are the advantages and disadvantages of each method? Be able to choose the...
