Homework #3
CS 539,
100 points total [6% of your final grade]
Delivery: Submit via Canvas
In this assignment, you will implement logistic regression with stochastic gradient descent in python3. In
stochastic gradient descent, you are supposed to update theta (i.e., w and b) by a training example (refer to
GD_vs_SGD.pdf or online resources).
In this problem, you will implement the logistic regression algorithm in python3. We provide the following files:
a) part1.py - You will implement several functions. Do not change the input and the output of the functions.
b) test1.py - This file includes unit tests. Run this file by typing ‘nosetests -v test1.py’ in the terminal. No
modification is required.
c) GD_vs_SGD.pdf – a pseudo code showing the difference between (batch) gradient descent and
stochastic gradient descent. This document is for your information.
What to turn in:
Submit to Canvas your part1.py.
This is an individual assignment, but you may discuss general strategies and approaches with
other members of the class (refer to the syllabus for details of the homework collaboration
policy).
