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# Table of contents
# Learn more at https://jupyterbook.org/customize/toc.html
format: jb-book
root: README.md
parts:
- caption: Things you should know
chapters:
- file: syllabus.md
- file: docs/README.md
- file: learning-objectives.md
sections:
- file: docs/330_vs_340.md
- file: docs/homework_instructions.md
- file: docs/resources.md
- file: docs/grades.md
- file: docs/setup.md
- file: docs/git_installation.md
- file: docs/asking_for_help.md
- caption: Lectures
chapters:
- file: lectures/notes/01_intro.ipynb
- file: lectures/notes/02_terminology-decision-trees.ipynb
- file: lectures/notes/03_ml-fundamentals.ipynb
- file: lectures/notes/04_kNNs-SVM-RBF.ipynb
- file: lectures/notes/04_kNNs-SVM-RBF.ipynb
- file: lectures/notes/05_preprocessing-pipelines.ipynb
# - file: lectures/notes/06_column-transformer-text-feats.ipynb
# - file: lectures/notes/07_linear-models.ipynb
# - file: lectures/notes/08_hyperparameter-optimization.ipynb
# - file: lectures/notes/09_classification-metrics.ipynb
# - file: lectures/notes/10_regression-metrics.ipynb
# - file: lectures/notes/12_ensembles.ipynb
# - file: lectures/notes/13_feat-importances.ipynb
# - file: lectures/notes/14_feature-engineering-selection.ipynb
# - file: lectures/notes/15_K-Means.ipynb
# - file: lectures/notes/16_DBSCAN-hierarchical.ipynb
# - file: lectures/notes/17_recommender-systems.ipynb
# - file: lectures/notes/18_natural-language-processing.ipynb
# - file: lectures/notes/19_intro_to_computer-vision.ipynb
# - file: lectures/notes/20_time-series.ipynb
# - file: lectures/notes/21_survival-analysis.ipynb
# - file: lectures/notes/22_communication.ipynb
# - file: lectures/notes/24_deployment-conclusion.ipynb
# - file: lectures/notes/final-exam-review-guiding-question.ipynb
# - file: lectures/notes/appendixA_feature-engineering-text-data.ipynb
# - file: lectures/notes/appendixB_multiclass-strategies.ipynb
- caption: Section slides
chapters:
- file: lectures/101&103-Giulia-lectures/README
sections:
- file: lectures/101-Giulia-lectures/01_intro.ipynb
- file: lectures/101-Giulia-lectures/02_terminology-decision-trees.ipynb
- file: lectures/101-Giulia-lectures/03_ml-fundamentals.ipynb
- file: lectures/101-Giulia-lectures/04_kNNs-SVM-RBF.ipynb
- file: lectures/101-Giulia-lectures/05_preprocessing-pipelines.ipynb
- file: lectures/101-Giulia-lectures/06_column-transformer-text-feats.ipynb
- file: lectures/101-Giulia-lectures/07_linear-models.ipynb
- file: lectures/101-Giulia-lectures/08_hyperparameter-optimization.ipynb
- file: lectures/101-Giulia-lectures/09_classification-metrics.ipynb
- file: lectures/101-Giulia-lectures/10_regression-metrics.ipynb
- file: lectures/101-Giulia-lectures/12_ensembles.ipynb
- file: lectures/101-Giulia-lectures/13_feat-importances
- file: lectures/101-Giulia-lectures/14_feature-engineering-selection
- file: lectures/101-Giulia-lectures/15_K-Means
- file: lectures/101-Giulia-lectures/16_DBSCAN-hierarchical
- url: "https://firasm.github.io/cpsc330-slides/slides-17"
title: Lecture 17
- url: "https://firasm.github.io/cpsc330-slides/slides-18"
title: Lecture 18
- file: lectures/101-Giulia-lectures/19_intro_to_computer-vision
- file: lectures/101-Giulia-lectures/20_time-series
- file: lectures/101-Giulia-lectures/21_survival-analysis
- file: lectures/101-Giulia-lectures/22_communication
- file: lectures/101-Giulia-lectures/lec23
title: Lecture 23
- file: lectures/102-Varada-lectures/README
sections:
- url: "https://kvarada.github.io/cpsc330-slides/lecture-01.html"
title: Lecture 1
- url: "https://kvarada.github.io/cpsc330-slides/lecture-02.html"
title: Lecture 2
- url: "https://kvarada.github.io/cpsc330-slides/lecture-03.html"
title: Lecture 3
- url: "https://kvarada.github.io/cpsc330-slides/lecture-04.html"
title: Lecture 4
- url: "https://kvarada.github.io/cpsc330-slides/lecture-05.html"
title: Lecture 5
#- url: "https://kvarada.github.io/cpsc330-slides/lecture-06.html"
# title: Lecture 6
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-07.html"
# title: Lecture 7
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-08.html"
# title: Lecture 8
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-09.html"
# title: Lecture 9
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-10.html"
# title: Lecture 10
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-11.html"
# title: Lecture 11
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-12.html"
# title: Lecture 12
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-13.html"
# title: Lecture 13
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-14.html"
# title: Lecture 14
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-15.html"
# title: Lecture 15
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-16.html"
# title: Lecture 16
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-17.html"
# title: Lecture 17
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-18.html"
# title: Lecture 18
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-19.html"
# title: Lecture 19
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-20.html"
# title: Lecture 20
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-21.html"
# title: Lecture 21
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-22.html"
# title: Lecture 22
# - file: lectures/102-Varada-lectures/lec23
# title: Lecture 23
# - url: "https://kvarada.github.io/cpsc330-slides/lecture-24.html"
# title: Lecture 24
- caption: Attribution
chapters:
- file: attribution
- file: LICENSE