KO | EN

GitLite

Minimalist Open Source Repository Search Engine

gitlite — search

#developer-tools #typescript #claude-code #codex #dsh #dsh-plugin #ai-agent #ai-agents #deepseek-harness #agent-skills #macos #cli

Coursera-MLOps-C2-lab4-greedy-optimization

★ 15 Open GitHub ↗

Greedy optimizations for Coursera MLOps course

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

## Lab: Greedy Optimization

### Overview

In this lab, you will work with a greedy change command-line tool and a traveling salesman algorithm. You will modify the command-line tool, reflect on its robustness, and explore ways to enhance the scripts.

### Goals

By the end of this lab, you will:

1. Understand how to modify command-line tools for improved robustness.
2. Learn how to enhance scripts for better performance and functionality.

### Tasks

#### A. Run the greedy change command-line tool

1. Run the greedy change command-line tool: `python greedy_coin.py 1.50`

2. Change the code to have a flag for dollars and flag for cents, i.e., `--dollars` and `--cents`.

**Reflection question:** Is this version of the command-line tool more robust against errors?

**Reflection question:** What could you build to enhance this script? Do it and add it to your portfolio.

#### B. Run the traveling salesman algorithm

1. Run the traveling salesman algorithm: `python tsp.py simulate`

2. What is the optimal number of simulations to run?

Coursera-MLOps-C2-lab4-greedy-optimization

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README