🌐Federated Learning

Training models across decentralized devices without sharing raw data.

🔢Few-Shot Learning

Learning from only a small number of labeled examples per class.

🎛️Fine-Tuning

Further training a pretrained model on a smaller task-specific dataset.

⚔️Generative Adversarial Network

Two networks compete: a generator creates data and a discriminator judges it.

🎨Generative AI

AI systems that can create new content such as text, images, or audio.

✨Generative Model

A model that learns to generate new data resembling its training set.

⛰️Gradient Descent

An optimization algorithm that iteratively minimizes a loss function.

🕸️Graph Neural Network

A neural network designed to operate on graph-structured data.

🎚️Hyperparameter

A configuration setting that controls the training process of a model.

🧩Image Segmentation

Partitioning an image into regions to identify objects and boundaries.

⚙️Inference

The process of using a trained model to make predictions on new data.

🧪Knowledge Distillation

Training a small model to mimic the behavior of a larger model.

🕸️Knowledge Graph

A structured representation of entities and their relationships.

🏷️Label

The known output or target value associated with a training example.

📖Large Language Model

A transformer-based model trained on massive text corpora.

👻Latent Variable

An unobserved variable inferred from data that influences outcomes.

🧠Long Short-Term Memory

A recurrent network architecture that learns long-range dependencies.

📏Loss Function

A function that measures the difference between predicted and actual values.

📈Machine Learning

A field where algorithms improve automatically through experience and data.

📦Model

A mathematical representation learned from data that makes predictions.

🗜️Model Compression

Techniques that reduce model size for faster and cheaper deployment.

🎭Multimodal Learning

Learning from and integrating multiple types of data like text and images.

🗣️Natural Language Processing

The field of enabling computers to understand and generate human language.

🔗Neural Network

A computing system inspired by biological neurons that learns from data.

🔲Object Detection

Identifying and locating objects within an image or video.

🗺️Ontology

A formal specification of concepts and relationships in a domain.

🔎Optical Character Recognition

Converting images of text into machine-encoded text.

🎯Overfitting

When a model learns training data too well and fails to generalize.

🎯Precision and Recall

Metrics that measure the accuracy and completeness of a classifier.

✍️Prompt Engineering

Designing inputs to guide a language model toward desired outputs.