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quizzes as pdfs and workbook

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@@ -22,11 +22,11 @@ While Google Colab already includes most packages that we need, should you requi
## Course Overview
For an optimal learning experience, the chapters from the [machine learning book](https://franziskahorn.de/mlbook/) should be interleaved with quizzes and programming exercises as shown below. Additionally, you should take notes in the workbook while working through the materials.
For an optimal learning experience, the chapters from the [machine learning book](https://franziskahorn.de/mlbook/) should be interleaved with quizzes and programming exercises as shown below. Additionally, you should take notes in the [workbook](/other/ml_course_workbook.pdf) while working through the materials.
**Important:** Please make note of all questions that arise while working through the materials. At the beginning of each group session, we'll collect everyone's questions and discuss them.
**Important:** Please make a note of all questions that arise while working through the materials. At the beginning of each group session, we'll collect everyone's questions and discuss them.
You can also find the course syllabus on the last page of the [course description](/ml_course_description.pdf), which explicitly lists all the sections of the book for each block.
You can also find the course syllabus on the last page of the [course description](/ml_course_description.pdf), which explicitly lists the sections of the book for each block.
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@@ -34,7 +34,7 @@ You can also find the course syllabus on the last page of the [course descriptio
##### Block 1.1:
- [ ] Read the whole chapter: ["Introduction"](https://franziskahorn.de/mlbook/_introduction.html)
- [ ] Answer [Quiz 1](https://forms.gle/uzdzytpsYf9sFG946)
- [ ] Answer [Quiz 1](https://forms.gle/uzdzytpsYf9sFG946) (quizzes are also available in PDF form in the folder "other" in case you can't access Google Forms)
##### Block 1.2:
- [ ] Read the whole chapter: ["ML with Python"](https://franziskahorn.de/mlbook/_ml_with_python.html)
@@ -59,7 +59,7 @@ You can also find the course syllabus on the last page of the [course descriptio
- [ ] Work through [Notebook 2: image quantization](/notebooks/2_image_quantization.ipynb) (after the section on clustering)
##### Block 2.2:
- [ ] Read the first sections of the chapter ["Supervised Learning"](https://franziskahorn.de/mlbook/_supervised_learning.html) up to and including ["Model Evaluation"](https://franziskahorn.de/mlbook/_model_evaluation.html)
- [ ] Start reading the first sections of the chapter ["Supervised Learning"](https://franziskahorn.de/mlbook/_supervised_learning.html) up to and including ["Model Evaluation"](https://franziskahorn.de/mlbook/_model_evaluation.html)
- [ ] Answer [Quiz 4](https://forms.gle/M2dDevwzicjcHLtc9)
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@@ -71,7 +71,7 @@ You can also find the course syllabus on the last page of the [course descriptio
- [ ] **In parallel**, work through the respective sections of [Notebook 3: supervised comparison](/notebooks/3_supervised_comparison.ipynb)
##### Block 3.2:
- [ ] Start with the chapter ["Deep Learning & more"](https://franziskahorn.de/mlbook/_deep_learning_more.html) up to and including the section: ["Information Retrieval (Similarity Search)"](https://franziskahorn.de/mlbook/_information_retrieval_similarity_search.html) and refresh your memory on the sections on [TF-IDF feature vectors](https://franziskahorn.de/mlbook/_feature_extraction.html) and [cosine similarity](https://franziskahorn.de/mlbook/_computing_similarities.html)
- [ ] Start reading the chapter ["Deep Learning & more"](https://franziskahorn.de/mlbook/_deep_learning_more.html) up to and including the section: ["Information Retrieval (Similarity Search)"](https://franziskahorn.de/mlbook/_information_retrieval_similarity_search.html) and refresh your memory about [TF-IDF feature vectors](https://franziskahorn.de/mlbook/_feature_extraction.html) and [cosine similarity](https://franziskahorn.de/mlbook/_computing_similarities.html)
- [ ] Work through [Notebook 4: information retrieval](/notebooks/4_information_retrieval.ipynb)
##### Block 3.3:
@@ -107,5 +107,6 @@ You can also find the course syllabus on the last page of the [course descriptio
- [ ] Answer [Quiz 5](https://forms.gle/uZGj54YQHKwckmL46)
- [ ] Read the whole chapter: ["Conclusion"](https://franziskahorn.de/mlbook/_conclusion.html)
- [ ] Complete the exercise: ["Your next ML Project"](/other/exercise_your_ml_project.pdf) (in case you need some inspiration for a project idea, have a look at [how ML could be used to fight climate change](https://www.climatechange.ai/summaries)). Feel free to prepare a few slides or use the [Word template](/other/exercise_your_ml_project_template.docx) and aim for a 5 minute presentation.
- [ ] Please fill out the [Feedback Survey](https://forms.gle/Ccv5h5zQxwPjWtCS7) to help me further improve this course! :-)
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