Exams  official list
General guide, mailing list archives
 Facebook Group Chat
 Honours hurdles: refer to your DRPS programme
INF2D  Reasoning and Agents piazza  drps, info, papers April/May exam
 MCQ Question Cache
 Quizlet
 Python implementation of algorithms from Russell And Norvig’s “Artificial Intelligence  A Modern Approach”
 AlphaBeta pruning interactive example
 Another AB pruning example  allowing you to create your own tree
 Good set of video lectures on most things covered in the course
 Breadth first search & depth first search
 PDDL Reference
INF2B  Algorithms, Data Structures and Learning piazza (learning)  drps, info, papers April/May exam
Learning
 What is a neural network? (3blue1brown)
 Using neural nets to recognise handwritten digits
 Revision Formulae for Learning Thread (pdf) (LaTex)
 Learning notes  Missing: perceptrons, singlelayer and doublelayer neural networks sections
 Pearson Correlation Coefficient
ADS
 Introduction to ADS (gitbook, non inf)
 Amazing interactive examples from from USFCA
 Wikibook covering most of the stuff we are doing
 Karatsuba Multiplication in 13 minutes (video, watchable at 1.25x)
Learning coursework
 MATLAB for use at home (free)
 Installing GNU Octave on macOS (much lighter than MATLAB)
 NumPy: quickstart tutorial
 Example Lab using numpy, scipy, pandas, and matplotlib: Similarity and recommender systems
 Why can’t I paste using Ctrl+V in MatLab???  The default settings are odd. Go to Preferences > MATLAB > Keyboard > Shortcuts, change Emacs Default Set to Windows Default Set.
 Run MATLAB scripts from the command line
 Relevant bits from Vision processing at Stanford:
 Interactive veronoi knn explorer
 Interactive SVM examples, similar to discriminant functions
 Linear classifiers the content seems to better explain the lectures on NN and discriminant functions
PWA  Probability with Applications piazza
 Summary
 Solutions: 9ed
 Cheat Sheet (source)
 Another cheat sheet with guides on distributions
 Joint probability distributions
 Conditional Probability Visualisation

A visual introduction to probability and statistics (Seeing Theory)
 Mostlycomplete notes
 Discrete probability: Missing combinatorics section.
 Continuous probability: Missing continuous markov chains, poisson processes, birthdeath processes etc.
 Videos
 Binomial probability (Khan Academy)
 Intro to Poisson distribution (jbstatistics)
 Intro to probability (followed by conditional probability)  playlist (Trefor Bazett)  this video to end of playlist
 Bayes Theorem ( Michel van Biezen)
 Calculators