Explore AIstify's latest reporting, research, and expert analysis tagged with "machine learning", collected in one continuously updated archive.
Semantic search uses embeddings to retrieve information by meaning and context, finding relevant results even when documents use different words.
Precision is the proportion of predicted positive cases that are actually positive.
Synthetic data is artificially generated information used to train, test, or evaluate AI systems when real data is limited, sensitive, or costly.
Fine-tuning adapts a pretrained AI model to a specific task, domain, or behavior by continuing training on targeted examples.
Regression is a supervised machine learning task that predicts continuous numerical values such as prices, demand, time, or risk.
The Yeo-Johnson transformation reshapes numerical data, including zero and negative values, to stabilize variance and support machine learning models.
A recurrent neural network (RNN) is a deep learning model that carries information across sequential inputs such as text, speech, and time-series data.
YARN is Hadoop’s resource-management and scheduling layer for running distributed data processing, analytics, and machine learning workloads.
Q-learning is a reinforcement learning algorithm that learns the long-term value of actions through rewards without requiring a model of the environment.
Multitask learning trains one model on several related objectives so shared representations can improve multiple tasks.
A Markov chain models transitions between states where the next state depends only on the current state.
Radical Ventures is a Canadian venture capital firm focused on artificial intelligence and deep technology companies.
Vector Institute is a Toronto-based nonprofit AI research institute supporting machine learning research, talent development, industry collaboration, and applied AI programs.
Mila is a Montreal-based artificial intelligence research institute known for machine learning, deep learning, academic research, education, and responsible AI initiatives.
Few-shot learning allows an AI model to recognize a task or pattern from only a small number of examples.