Abridged List of Machine Learning Topics

Interesting list published on Startup.ml. Here are the main categories:

  1. Deep Learning
  2. Online Learning
  3. Graphical Models
  4. Structured Predictions
  5. Ensemble Methods
  6. Kernel Machines
  7. Hyper-parameter Optimization
  8. Optimization
  9. Graphs
  10. Hadoop / Spark
  11. GPU learning
  12. Julia
  13. Robotics
  14. Natural Language Processing
  15. Visualization
  16. Computer Vision

Each section features software, research and lectures. Here's their selection for deep learning:


  • Vowpal Wabbit (VW) – a fast out-of-core learning system that serves as a research vehicle on online learning, reductions, cluster parallel and other areas.
  • Sofia-ML – Suite of Fast Incremental Algorithms for Machine Learning. Includes methods for learning classification and ranking models, using Pegasos SVM, SGD-SVM, ROMMA, Passive-Aggressive Perceptron, Perceptron with Margins, and Logistic Regression.


  • Agarwal, Alekh, et al. "A reliable effective terascale linear learning system." arXiv preprint arXiv:1110.4198 (2011).


  • Langford, John, LeCun, Yann. "Large-Scale Machine Learning"

A few categories are missing, including feature selection, scoring models, neural networks, and association rules. But it's a great resource nevertheless.

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