Courses 2021-22



Resources



Assignments

Note: If an assignment does not have a link, then it was written on the board, and it can be found in the "Board Pictures" photo album in your respective grade level (on this page, above).

Computation & Modeling
Machine Learning (11th Grade)
Machine Learning (12th Grade)
Continue set 31
Evolving Neural Nets
Continue Blondie24 Project
Set 31: Snake
Space Empires - combat phase
Continue Blondie24 Project
Set 30: Connect Four Custom Strategy
Simplex Method - matrix operations and implementation
Continue Blondie24 Project
Set 29: Connect Four
Space Empires
Part 3 of Blondie24 Project
Set 28: Tic-Tac-Toe Competition
Close the loop on genetic algorithms, begin Simplex Method
Finish part 2 and begin part 3 of Blondie24 Project
Set 27: Tic-Tac-Toe Game Tree
Space Empires
Blondie24 Project - parts 1 and 2
Set 26: Custom Tic-Tac-Toe Strategy (plus some other small exercises)
Space Empires
Finish GA 2.0
Set 25: Dijkstra's Algorithm
GA 2.0: Continued genetic algorithms on tic-tac-toe: tournament selection, tournament fitness, mutation rates
GA 2.0: Continued genetic algorithms on tic-tac-toe: tournament selection, tournament fitness, mutation rates
Set 24: Tic-Tac-Toe with Random Players
GA 1.0: Intro to genetic algorithms on tic-tac-toe
GA 1.0: Intro to genetic algorithms on tic-tac-toe
Set 23: Distance and Shortest Path in Graphs, Data Normalization
Space Empires
Space Empires
Set 22: Cross-Validation with KNN, Exam Prep
EXAM FRIDAY! Topics include multivariable gradient descent, fitting regressions via gradient descent on RSS, SQL (join, group by, subqueries), Euler estimation for systems of differential equations, k-means and elbow method, anything from last semester's final.
Beginning shared implementation of Space Empires
EXAM FRIDAY! The main topic is neural networks - direct differentiation, backpropagation, good vs bad activation functions, etc. Plus anything from last semester's final.
Space Empires
EXAM FRIDAY! Topics include PCA, fitting models to general data sets (mini kaggle), simplex method, Q-learning, anything from last semester's final.
Set 21: Overfitting, Underfitting, Cross-Validation
EXAM NEXT FRIDAY! (2/25)
Neural net regressor with multiple hidden layers
EXAM NEXT FRIDAY! (2/25)
Intro to Q-learning
EXAM NEXT FRIDAY! (2/25)
Set 20: SQL, Haskell
Space Empires - begin shared implementation Space Empires - testing random player on economic phase; introduce planets/asteroids
Set 19: Elbow Method, SQL
Implement backpropagation algorithm in hard-coded neural net Simplex method
Set 18: K-Means, Self Joins, Haskell
Finish Space Empires competition, intro to backpropagation algorithm Space Empires - combat / economic phase log & random strategy development for simulation testing
Set 17: Generalizing Euler Estimator to Systems of Differential Equations
Space Empires - economic phase strategy development + competition Mini kaggle competition (on a toy dataset generated by the instructor)
Set 16: SQL, Logistic Regression via Gradient Descent, Euler Estimation
Regressing a linear combination of nonlinear functions via neural network Space Empires
Set 15: Linear and Polynomial Regression via Gradient Descent
Final exam corrections; Space Empires - economic phase Final exam corrections; principal component analysis
Set 14: SQL, Multivariable Gradient Descent
Benefits of gradient descent over transformations into linear space: power regression and exponential regression Benefits of gradient descent over transformations into linear space: power regression and exponential regression
Set 13: SQL, Gradient Descent, Operator Overloading, kNN
Space Empires Competition 2 Space Empires
Set 12: DataFrames from Scatch
Neural Nets: forward propagation by hand with simple activation f(x) = 2x, classification boundaries with arbitrary activation functions Keras: https://www.tensorflow.org/tutorials/keras/classification (for each tutorial we cover, walk through it and be ready to discuss it the following day)
Set 11: Logistic Regression with General Bounds + Data Set Analysis using DataFrames
• Exam Friday (11/12) - sorting algorithms, newton-rhapson, recursive vs non-recursive matrix determinant, linear/logistic regression, breadth-first and depth-first traversals
• Space Empires - first competition
• Exam Friday (11/12) - multivariable gradient descent, interpreting/predicting plots of running ML algorithms on data sets with particular features; random forests (11th only) and backpropagation algorithm (12th only)
• Neural net plots using sklearn implementations
• Exam Friday (11/12) - multivariable gradient descent, interpreting/predicting plots of running ML algorithms on data sets with particular features; random forests (11th only) and backpropagation algorithm (12th only)
Set 10: Interaction Terms and Intro to DataFrames
• Exam NEXT Friday (11/12)
• Space Empires
• Exam NEXT Friday (11/12)
• Space Empires
• Exam NEXT Friday (11/12)
Set 9: Regression with Multiple Inputs, Breadth-First and Depth-First Traversals, Intro to DataFrames Plots using artificial data set and sklearn implementations of kNN, decision tree, random forest Plots using artificial data set and sklearn implementations of kNN, decision tree, random forest
Set 8: Determinant via RREF, Merge Sort, Intro to Graphs Space Empires - running standardized strategies on each other's games Space Empires - visualization
Set 7: Linear and logistic regressor classes Implement random forests Implement backpropagation
Set 6: Matrix Inverse Space Empires - standardize strategy class Space Empires - get core game engine running
Continue set 5
Decision tree pruning Implement bias nodes and learn about activation functions
Set 5: RREF Algorithm
• Space Empires - write tests
• Exam Thursday (9/23) - gradient descent, bias-variance tradeoff, decision trees (11th) and neural nets (12th)
• Space Empires - coordinate to get tests working
• Exam Thursday (9/23) - gradient descent, bias-variance tradeoff, decision trees (11th) and neural nets (12th)
Set 4: Generalized Matrix Arithmetic, Newton-Rhapson, Merging
• Finish up set 2, and then continue Space Empires development - creates strategy players
• Exam NEXT Thursday (9/23) - gradient descent, bias-variance tradeoff, decision trees
• Finish up set 2, and then continue Space Empires development - coordinate to write tests
• Exam NEXT Thursday (9/23) - gradient descent, bias-variance tradeoff, neural nets
Set 3: Basic Sorting and Matrices Set 2: Decision Trees Set 2: Intro to Neural Nets
Set 2: Brute-Force Search, Bisection Search, Intro to Data Structures and Sorting Space Empires development - refactor and extend game to multiple ship types Space Empires development - begin rewriting in Javascript
Set 1: Some Basic Problems Set 1: Quant Review in Julia Set 1: Quant Review in Julia