1 / 5

Homework

Get help with homework questions about coding and find guidelines for your project proposal. We provide brief explanations and offer partial credit. No class next Monday, but we're available via email. Project ideas and research possibilities also provided.

hazelcole
Download Presentation

Homework

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Homework • Homework #1 is up • Programming Language: whatever • Write your own code • HW questions about code: Be succinct and clear • Partial credit will be given • So briefly justifying your answers may help

  2. Look at the homework early, because… • No class next Monday • Your TA is out next week • In the meantime, we’re both available via e-mail

  3. Project Guidelines • Project proposal due October 16 (~1 pg) • Who is in your group • Your task (and why is it interesting?) • Where did/will you get your data? • Which ML algorithms will you try first? • Final project write-up due December 8th • Web page • Report (~4 pgs, ACM format…link on course page)

  4. Some project ideas • The “standard” problems • Handwriting, text classification, disease detection, etc.; see the UCI ML repository • Recommendations • E.g., the Netflix prize • Sports predictions • Question: how does “intransitivity” impact ML? • Multi-task learning • TinyGrams • Google n-grams corpus gives P(phrase) for up to 5-word phrases • Based on 1 trillion words: unprecedented coverage • But around 150G uncompressed – could an ML approximation fit in memory?

  5. More “researchy” projects • A couple of project ideas related to information extraction • Example: TextRunner • If interested, drop me an e-mail (soon)

More Related