APPLIED MACHINE LEARNING
ArtificialGate | Dr. Barak Or
Student practice resources | 7 October 2026

This pack accompanies Modern Machine Learning, 2027 Edition, academic
revision dated 6 October 2026. The current complete textbook has 519 pages.
The LMS chapter reading lists use that revision's current page map.

Each of the 13 chapters has three learner notebooks:
  A_Practice: first core exercise.
  B_Practice: second core exercise.
  Case_Study_Practice: a named real-data investigation.

HOW TO START
1. Extract the ZIP on your computer.
2. Open Google Colab at https://colab.research.google.com/.
3. Choose File > Upload notebook and select a .ipynb file.
4. Read the notebook's setup and data instructions before running cells.
5. Work through A, then B, then the case study. Complete the TODO sections;
   these learner notebooks are intentionally not completed solutions.
6. Download your completed notebook and retain its experiment settings,
   metrics and failure analysis. Follow the LMS chapter completion checklist.

DATA AND REPRODUCIBILITY
Some notebooks fetch public datasets and require internet access. Follow the
dataset-specific provenance, licensing and setup notes. Teaching fixtures are
not substitutes for industry benchmarks. Record package versions and seeds.
Medical benchmark datasets are for methodological education, not diagnosis.

READING LINKS
The textbook PDF is a separate resource; it is not included in this ZIP.
Offline relative navigation links may depend on the original complete book
package. Use the LMS chapter reading list when those links are unavailable.
Notebook reading references identify the current 519-page academic revision.

READINESS
This pack contains 39 learner notebooks, not 39 finished assignments or
recorded videos. Original solution notebooks and instructor answer keys are
not included. Selected solutions were tested locally in the book workflow;
this pack has not been validated by executing every learner notebook in a
fresh hosted Google Colab environment. Do not interpret quiz scores as a
validated professional certification or independent proof of mastery.

Textbook SHA-256:
12cb80f2f2bd037839f6670373efe026e6b2e1eb4117bfdd36da177f7b40fade
