The repository contains all the source files for the Regression Cookbook (Now with Machine Learning and Stats Flavours!). This textbook aims to set a common ground between machine learning and statistics regarding linear regression techniques using Python and R under two perspectives: inference and prediction.
[x] Given its length, Section 1.2 (A Quick Review on Probability and Frequentist Statistical Inference) will have its chapter (i.e., Chapter 2). Therefore, writing and sections should be moved and modified accordingly.
[x] Since there will be a new Chapter 2, Chapter 1's intro will be rewritten accordingly.
[ ] Continue writing the basics of probability.
[ ] Explore how to incorporate live dashboards in the textbook's website.
@phchen5
[ ] Continue with the writing of Section 1.3 (The Data Science Workflow):
We can check the notes from DSCI 562 in lecture1 to get some ideas on what the plan is for this section. That said, it'd be ideal to support the writing with further literature references.
For instance, the book The Art of Data Science might be a good starting point to find further references. Also, the references from the MDS' visualization courses would be another starting point.
[ ] Explore AI-based simulated dataset generators so we can incorporate these datasets into all main chapters. We agreed on not using a single big dataset for all the chapters but datasets whose main premise should somehow match (to keep consistency across all chapters in terms of the main inquiries we would try to address).
@andytai7
[ ] Continue with the writing of Section 1.3 (The Data Science Workflow):
We can check the notes from DSCI 562 in lecture1 to get some ideas on what the plan is for this section. That said, it'd be ideal to support the writing with further literature references.
For instance, the book The Art of Data Science might be a good starting point to find further references. Also, the references from the MDS' visualization courses would be another starting point.
[ ] Explore AI-based simulated dataset generators so we can incorporate these datasets into all main chapters. We agreed on not using a single big dataset for all the chapters but datasets whose main premise should somehow match (to keep consistency across all chapters in terms of the main inquiries we would try to address).
[x] To reduce the number of colours in the callout blocks (Definition, Note, and Tip) from their red, blue, and green states to a shade of blues. We would need to modify the file custom.css accordingly.
Meeting date: Monday, August the 12th, 2024.
Action items:
@alexrod61
@phchen5
lecture1
to get some ideas on what the plan is for this section. That said, it'd be ideal to support the writing with further literature references.@andytai7
lecture1
to get some ideas on what the plan is for this section. That said, it'd be ideal to support the writing with further literature references.custom.css
accordingly.