NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information. | |

Fall 2020 Computer Science and Operations Research W4246 section 001 ALGORITHMS FOR DATA SCIENCE ALGORITHMS FOR DATA SCIEN | |

Call Number | 10808 |

Day & Time Location |
TR 10:10am-12:55pm ONLINE ONLY |

Points | 3 |

Grading Mode | Standard |

Approvals Required | None |

Instructor | Eleni Drinea |

Type | LECTURE |

Method of Instruction | On-Line Only |

Course Description | Prerequisites: basic knowledge in programming (e.g. at the level of COMS W1007), a basic grounding in calculus and linear algebra. Methods for organizing data, e.g. hashing, trees, queues, lists,priority queues. Streaming algorithms for computing statistics on the data. Sorting and searching. Basic graph models and algorithms for searching, shortest paths, and matching. Dynamic programming. Linear and convex programming. Floating point arithmetic, stability of numerical algorithms, Eigenvalues, singular values, PCA, gradient descent, stochastic gradient descent, and block coordinate descent. Conjugate gradient, Newton and quasi-Newton methods. Large scale applications from signal processing, collaborative filtering, recommendations systems, etc. |

Web Site | Vergil |

Subterm | 10/26-12/14 (B) |

Department | Computer Science |

Enrollment | 129 students (140 max) as of 7:34PM Wednesday, February 24, 2021 |

Subject | Computer Science and Operations Research |

Number | W4246 |

Section | 001 |

Division | Interfaculty |

Campus | Morningside |

Section key | 20203CSOR4246W001 |

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