Fall 2020 | CSE 103 (remote) | Probability and statistics for computer scientists |

Fall 2020 | CSE 291 (remote) | Probabilistic approaches to unsupervised learning |

Spring 2021 | CSE 101 (remote) | Algorithms |

Spring 2021 | CSE 291 (remote) | Continual learning |

Webpages of some courses from previous years:

CSE 101 | Algorithms |

CSE 103 | Probability and statistics |

CSE 151 | Machine learning |

CSE 250B | Machine learning |

CSE 254 | Seminar: inference in graphical models |

CSE 254 | Seminar: embeddings |

CSE 254 | Seminar: deep learning |

CSE 254 | Seminar: neurally-inspired unsupervised learning |

CSE 254 | Seminar: deep unsupervised learning |

CSE 291 | Probabilistic AI |

CSE 291 | Learning theory I (supervised learning) |

CSE 291 | Topics in unsupervised learning |

CSE 291 | Bayesian methods |

CSE 291 | Geometric algorithms |

CSE 291 | Topics in learning theory |

CSE 291 | Distances, similarities, and embeddings |