{"id":144,"date":"2020-10-28T07:46:11","date_gmt":"2020-10-28T06:46:11","guid":{"rendered":"https:\/\/user.phil.hhu.de\/ehren\/?page_id=144"},"modified":"2021-04-20T09:15:53","modified_gmt":"2021-04-20T07:15:53","slug":"vector-semantics-winter-2020-21","status":"publish","type":"page","link":"https:\/\/user.phil.hhu.de\/ehren\/vector-semantics-winter-2020-21\/","title":{"rendered":"Vector Semantics – Winter 2020\/21"},"content":{"rendered":"\n

Course Material<\/h3>\n
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  1. Course Info: Screencast<\/a>, Slides<\/a><\/li>\n
  2. Basics: Screencast<\/a>, Slides<\/a><\/li>\n
  3. Linear Algebra I: Screencast<\/a>, Slides<\/a>, Homework 1<\/a><\/li>\n
  4. Linear Algebra II: Screencast<\/a>, Slides<\/a>, Homework 2<\/a> , Solutions to homework 1 (as a notebook)<\/a>, Notebook on linear transformations<\/a>, Linear Transformations and Video Games<\/a><\/li>\n
  5. Building Distributional Models: Screencast<\/a>, Slides<\/a>, Homework 3<\/a>, Solutions to homework 2 (as a notebook)<\/a><\/li>\n
  6. SVD: Screencast<\/a>, Slides<\/a>, Notebooks: Numpy<\/a>, PCA<\/a>, SVD and LSI<\/a><\/li>\n
  7. Distributional Memory: Screencast<\/a>, Slides<\/a>, Homework 4<\/a><\/li>\n
  8. Building a Distributional Model (Demo): Screencast<\/a>, Notebook<\/a>, RG-65 Dataset<\/a>, Glove Vectors<\/a><\/li>\n
  9. Linear Regression: Screencast I (Theory)<\/a>, Screencast II (Praxis)<\/a>, Slides<\/a>, Notebook<\/a>, Example dataset<\/a>, Homework 5<\/a><\/li>\n
  10. Multivariate Linear Regression\/Logistic Regression: Screencast<\/a>, Slides<\/a>, Homework 6<\/a>, Solution to ex. 1 of Homework 5<\/a><\/li>\n
  11. Neural Nets: Screencast<\/a>, Slides<\/a>, Video on Neural Nets by 3Blue1Brown<\/a>, Homework 7<\/a>, Solution to ex. 1 and 4 of Homework 6<\/a>, Notebook on Logistic Regression<\/a>, Screencast on Logistic Regression Notebook<\/a><\/li>\n
  12. Word2vec: Screencast<\/a>, Slides<\/a>, Solution to ex. 1 of Homework 7<\/a>, Homework 8<\/a><\/li>\n
  13. Backpropagation: Screencast<\/a>, Slides<\/a> (6 – 43), Video on derivatives (Khan academy)<\/a>, Video on chain rule (Khan academy)<\/a>, Original Video on Backpropagation<\/a> (Andrej Kaparthy, 1:35 – 29:00 min), Homework 9<\/a>, Solution to Homework 8<\/a>, Solution to Homework 9<\/a><\/li>\n<\/ol>\n

    Errata<\/h3>\n