A branch of computer science which aims to simulate human intelligence and problem-solving capabilities in machines.
Decoder
In natural language processing (NLP), a decoder is a component of a neural network that takes the encoded representations generated by the encoder and produces an output sequence, typically in the form of text or structured data. The decoder translates the encoded information into a format that is understandable for humans, such as a translation in a language translation task or a response in a chatbot application.
Deep Learning (DL)
A branch of machine learning that uses multiple layers of artificial neural networks to learn from data.
Encoder
In natural language processing (NLP), an encoder is a component of a neural network that transforms input text into a format that the model can understand and process. It converts words or characters into numerical representations, typically using techniques like word embeddings. This numerical representation captures semantic and syntactic information about the text, allowing the model to learn patterns and relationships between words or characters.
Generative AI (GenAi)
A subset of AI capable of creating new content (text, images, audio, videos etc.) that resembles real-world data.
Hugging Face
Hugging Face, Inc. is a company from New York City that makes tools for building apps with machine learning. It is known for its transformers library, used for language processing, and the platform where people can share ML models and data.
Machine Learning (ML)
A subfield of artificial intelligence that uses algorithms that learn from patterns in data to make predictions without being explicitly programmed.
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a field of artificial intelligence (AI) that focuses on enabling computers to understand, interpret, and generate human language in a way that is both meaningful and useful. It involves tasks such as text classification, sentiment analysis, language translation, and speech recognition.
Neural Network (NN)
A group of interconnected artificial neurons that teaches computers to process data in a way that is inspired by the neurons in the human brain.
Reinforcement Learning from Human Feedback (RLHF)
A machine learning technique where an agent learns from feedback directly provided by humans instead of predefined rewards. This approach helps machines learn effectively in complex environments where traditional signals may be sparse or unreliable.
Transformer
A deep learning model designed for various NLP tasks, such as language translation, text summarization, and language understanding. It relies on a mechanism called self-attention to process input sequences and capture relationships between different words or tokens.