Similarity learning
Definition
Similarity learning focuses on training models to map inputs into a vector space where …
Deep Learning
Sentence Transformers
Definition
Sentence Transformers are extensions of traditional Transformer models (like BERT) …
Pyannote Audio
Definition
Pyannote Audio is a comprehensive toolkit designed to facilitate the development and …
Mode Collapse
Definition
In GANs, mode collapse occurs when the generator learns to exploit weaknesses in the …
Hardware for artificial intelligence
Definition
AI hardware refers to specialized computing devices optimized for the massive parallel …
Gradient Accumulation
Definition
This optimization strategy allows deep learning models to be trained with effective batch …
Gated Recurrent Unit
Definition
A Gated Recurrent Unit (GRU) is a specialized recurrent neural network (RNN) cell …
Feature learning
Definition
Feature learning, often associated with deep learning, enables models to learn …
Domain Adaptation
Definition
Domain adaptation addresses the challenge when training and testing data come from …
Double Descent
Definition
Double descent challenges the traditional bias-variance tradeoff by showing that highly …
Bert
Definition
BERT is a transformer-based machine learning technique for NLP pre-training developed by …
Batch Normalization
Definition
This method adjusts and scales activations to have zero mean and unit variance within …
Recurrent Neural Network
Definition
RNNs are designed to recognize patterns in sequences of data, such as text, genomes, …
ReLU
Definition
ReLU is widely used in deep learning neural networks due to its computational efficiency …
Dropout
Definition
In neural networks, dropout prevents overfitting by temporarily removing a random subset …
Pre-training
Definition
Pre-training is a foundational technique in deep learning where a model learns broad …
Neural Network
Definition
A neural network is a series of algorithms that endeavors to recognize underlying …
Large Language Model
Definition
Large Language Models (LLMs) are advanced artificial intelligence systems based on …
Adam
Definition
Adam (Adaptive Moment Estimation) is a popular first-order gradient-based optimization …
Fine-tuning
Definition
Fine-tuning involves taking a model already trained on a large, general dataset and …