AI Concepts
DBSCAN can identify noise without choosing a cluster count first
DBSCAN builds clusters from local density and can leave points unassigned. Understand eps, min_samples and the limits before interpreting the labels.
AI · VISION · EVERYDAY SYSTEMS
machine learning
Model Evaluation
Learning curves help you question whether the next experiment needs more data
Learning curves compare training and validation scores as the training set grows. Use them to plan the next experiment without treating one plot as a verdict.
AI Evaluation
A Random Seed Helps Repeat an AI Experiment, but Does Not Guarantee Identical Results
Record the environment and sources of randomness alongside a seed when comparing machine-learning experiments.
AI Concepts
Reading Embeddings Without Inventing Names for Every Dimension
Understand an embedding as a learned numerical representation without assuming each coordinate has a tidy human-readable meaning.
Applied AI
An AI Test Can Look Excellent Because It Has Seen the Answers
Spot machine-learning data leakage by checking when information became available and keeping test data out of model preparation.