Materials

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Assignment0_data (2.7 MB, rev 1) Assignment 0 - Notebooks and Data
Assignment0_handout (179 KB, rev 2) Assignment 0 - Problem Set
Assignment0_solution_programming (2.5 MB, rev 1) Assignment 0 - Sample solution practical problems
Assignment0_solution_theory (224 KB, rev 1) Assignment 0 - Sample solution theoretical problems
Assignment1_data (5.9 KB, rev 1) Assignment 1 - Notebooks and Data
Assignment1_handout (209 KB, rev 1) Assignment 1 - Problem Set
Assignment2_data (4.4 MB, rev 1) Assignment 2 - Notebooks and Data
Assignment2_handout (236 KB, rev 2) Assignment 2 - Problem Set
Assignment3_data (20 KB, rev 1) Assignment 3 - Notebooks and Data
Assignment3_handout (192 KB, rev 4) Assignment 3 - Problem Set
Assignment4_data (229 KB, rev 1) Assignment 4 - Notebooks and Data
Assignment4_handout (291 KB, rev 1) Assignment 4 - Problem Set
Assignment5_data (17 KB, rev 2) Assignment 3 - Notebooks and Data
Assignment5_handout (337 KB, rev 4) Assignment 5 - Problem Set
Assignment6_data (89 KB, rev 1) Assignment 6 - Notebooks and Data
Assignment6_handout (324 KB, rev 1) Assignment 6 - Problem Set
code-of-conduct (63 KB, rev 1) Code of Conduct

Assignment1_classwork (151 KB, rev 3) Tutorial exercise sheet for Assignment1 (ungraded)
Assignment2_classwork (176 KB, rev 2) Tutorial exercise sheet for Assignment2 (ungraded)
Assignment3_classwork (145 KB, rev 1) Tutorial exercise sheet for Assignment 3 (ungraded)
Assignment4_classwork (189 KB, rev 1) Tutorial exercise sheet for Assignment 4 (ungraded)
Assignment5_classwork (460 KB, rev 2) Tutorial exercise sheet for Assignment 5 (ungraded)
Assignment6_classwork (310 KB, rev 3) Tutorial exercise sheet for Assignment6 (ungraded)

Beyond Linear (439 KB, rev 1) Lecture Recap for Beyond Linear
Bias & Variance (2.9 MB, rev 1) Lecture Recap for Bias & Variance
Classification 1 (3.2 MB, rev 1) Lecture Recap Classification 1
Classification 2 (5.5 MB, rev 1) Lecture Recap Classification 2
Clustering (986 KB, rev 1) Lecture Recap for Clustering
Dimensionality Reduction (1.6 MB, rev 1) Lecture Recap for Dimensionality Reduction
Generalization (329 KB, rev 1) Lecture Recap Generalization
LinearRegression 1 (1.6 MB, rev 1) Lecture Recap for Linear Regression 1
LinearRegression 2 (1.9 MB, rev 1) Lecture Recap for Linear Regression 2
Regularization (392 KB, rev 1) Lecture Recap for Regularization
Support Vector Machines (474 KB, rev 2) Lecture Recap for Support Vector Machines
Trees and Forests (301 KB, rev 1) Lecture Recap for Trees and Forests

00_slides (759 KB, rev 1) Lecture 0 - Organisation - Slides
01_slides (25 MB, rev 2) Lecture 1 - Bias and Variance - Slides
02_slides (4.1 MB, rev 1) Lecture 2 - Linear Regression I - Slides
03_slides (3.1 MB, rev 1) Lecture 3 - Linear Regression II - Slides
04_slides (3.7 MB, rev 2) Lecture 4 - Classification I - Slides
05_slides (7.4 MB, rev 1) Lecture 5 - Classification II - Slides
06_slides (15 MB, rev 1) Lecture 6 - Generalization - Slides
07_slides (4.3 MB, rev 3) Lecture 7 - Regularization - Slides
08_slides (1.4 MB, rev 1) Lecture 8 - Beyond Linear - Slides
09_slides (3.8 MB, rev 1) Lecture 9 - Dimensionality Reduction - Slides
10_slides (2.3 MB, rev 1) Lecture 10 - Clustering - Slides
11_slides (1.5 MB, rev 1) Lecture 11 - Trees and Forests - Slides
12_slides (1.7 MB, rev 1) Lecture 12 - Support Vector Machines - Slides
13_slides (4.0 MB, rev 1) Lecture 13 - Neural Networks - Slides
14_slides (1.3 MB, rev 1) Lecture 14 - ML and the Real World - Slides

eml23-exam1-questions (999 KB, rev 1) EML 23 – Exam 1 – Questions
eml23-exam1-solutions (1.1 MB, rev 1) EML 23 – Exam 1 – Answers

An Introduction to Statistical Learning with Applications in Python Main text book for the course
Fairness and Machine Learning Optional Reading for Lecture 14
The Algorithmic Foundations of Differential Privacy Optional Reading for Lecture 14
The Elements of Statistical Learning (2nd Edition) Auxiliary text book for the course
The Sound of Machine Learning The Sound of Machine Learning (that is just logistic regression)
Visualizing Data using t-SNE Additional Reading for Lecture 9 – Dimensionality Reduction

eml23-exam2-questions (964 KB, rev 1) EML 23 – Exam 2 – Questions
eml23-exam2-solutions (1.2 MB, rev 2) EML 23 – Exam 2 – Answers

eml20-exam1-questions (266 KB, rev 1) EML 20 – Exam 1 – Questions
eml20-exam1-solutions (285 KB, rev 1) EML 20 – Exam 1 – Solutions
eml20-exam2-questions (294 KB, rev 1) EML 20 – Exam 2 – Questions
eml20-exam2-solutions (420 KB, rev 1) EML 20 – Exam 2 – Solutions
eml21-exam1-questions (297 KB, rev 1) EML 21 – Exam 1 – Questions
eml21-exam1-solutions (411 KB, rev 2) EML 21 – Exam 1 – Solutions
eml21-exam2-questions (507 KB, rev 1) EML 21 – Exam 2 – Questions
eml21-exam2-solutions (656 KB, rev 1) EML 21 – Exam 2 – Solutions
eml22-exam1-questions (404 KB, rev 1) EML 22 – Exam 1 – Questions
eml22-exam1-solutions (376 KB, rev 1) EML 22 – Exam 1 – Solutions
eml22-exam2-questions (682 KB, rev 1) EML 22 – Exam 2 – Questions
eml22-exam2-solutions (783 KB, rev 1) EML 22 – Exam 2 – Solutions

icon_pdf (7.7 KB, rev 1) Icon for links to PDF files
icon_youtube (7.7 KB, rev 1) Icon for links to YouTube
icon_zoom (1.3 KB, rev 1) Icon for links to Zoom meetings

All electronic documents for this lecture are made available exclusively for your studies and must not be forwarded, nor reproduced, nor used in other documents. Individual figures may originate from copyrighted sources even when not explicitly designated as such.

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