machine learning

10 articles · All tags

• Open Datasets for Machine Learning: The Essential Landscape
  The open datasets that built modern machine learning — ImageNet to Common Crawl — where to find them, their licenses, and how to choose one for your project.
• Cross-Validation
  Resampling techniques for estimating how well a model performs on unseen data, most commonly k-fold cross-validation.
• k-Means Clustering
  An unsupervised learning algorithm that partitions data into k clusters by iteratively assigning points to the nearest centroid.
• k-Nearest Neighbors
  A simple instance-based machine learning algorithm that classifies or regresses by majority vote among the k closest training examples.
• Optical Character Recognition
  The conversion of images of text — scans, photographs, screenshots — into machine-readable text.
• Word Embeddings
  Dense vector representations of words learned from text, in which semantically similar words have similar vectors.
• Reinforcement Learning
  How agents learn from rewards and punishments through trial and error: Markov decision processes, value functions, and policy learning.
• Decision Trees and Random Forests
  Interpretable rule-based models built by recursive splitting, and the forests of randomized trees that made them competitive.
• Overfitting and Regularization
  When models memorize instead of generalize, and the standard techniques — from data to penalty terms — that prevent it.
• Gradient Descent
  The iterative optimization algorithm at the heart of training machine learning models: how it works, its variants, and its pitfalls.