CS167 Machine Learning

Course materials and notes for Drake University's CS167: Machine Learning

Instructor:

Meredith Moore
Assistant Professor of Computer Science
325 Collier Scripps Hall
meredith.moore@drake.edu

Office Hours

Monday-Thursday: 2:00pm - 3:30pm
Join Now! | Schedule

CS Tutors:

Tutors are free and Zoom appointments can be made at the Tutoring Website

Welcome to CS167

This website is where you will be able to find course resources like code, assignments and slides. The schedule below will be kept up to date.

Everything is currently under construction, so hard hats on 👷 –proceed with caution 🏗️ 🚧

Syllabus:

Fall 2021 Syllabus

Trying to link to Syllabus

Schedule 📆

Week Topics Date Assigned Due
1 Intro to Machine Learning
Python and Pandas Review
  SE1
 
2 Python, Pandas
K-Nearest Neighbors
  N1
SE1
3 kNN Implementation
w-kNN Normalization and Graphs
  SE2
N2
N1
SE2
4 Metrics and Testing
Decision Trees
  SE3
N3
N2, SE3
5 Introduction to Scikit-Learn
Random Forests
  SE4
N4
N3,
SE4
6 Midterm Review
Midterm (take home)
     
7 Random Forests
Project #1
  P1
N4
8 Support Vector Machines
Principal Component Analysis
  SE5

SE5
9 Linear Models: Perceptron, SGD
Multilayer Perceptrons
  SE6
N5

P1, SE6
10 Convolutional Neural Networks I
Convolutional Neural Networks II
  N6
N5
11 Recurrent Neural Networks   SE7
N7

SE7
12 Natural Language Processing   SE8

N7,SE8
13 Exam #2 Review
Exam #2 (take home)
  E2
P2

E2
14 Advanced Machine Learning Techniques
(GANs, Autoencoders, Speech Processing)
   
P2
15 Finals week (no final in this class)      

Syllabus ☑️

FAQ ❓

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