Machine Learning Research at Johns Hopkins



Thanks to Hal Daume for compiling most of this list.
  • GRMM: A graphical models package add-on for mallet
  • FastDT: Very fast decision tree learner that implements bagging and boosting
  • libSVM: a very efficient library for SVMs, available in C and Java
  • Mallet: a library for tons of NLP applications, including structured prediction with HMMs/CRFs, classification, clustering, topic modeling
  • MegaM: Optimization software for maximum entropy models, uses conjugate gradient for binary/binomial problems and LM-BFGS for multiclass problems
  • MinorThird: An NLP learning package that supports many standard algortihms
  • NLTK: A super-easy to use Python implementation of many popular NLP algorithms
  • SVM-Light: a super fast efficient library for SVMs. Supports ranking problems and kernels.
  • Torch3: a generic machine learning library, particularly good for neural networks
  • Weka: the "defacto" machine learning/datamining library

Machine Learning Courses

There are numerous machine learning courses offered at the undergraduate and graduate levels. Many courses post notes and slides that are useful for studying.

Links from the Johns Hopkins Library

Related Courses at Johns Hopkins

In addition to previous versions of this course, there are many other relevant courses at Johns Hopkins. See here for a full list.