abner0214/basic_machine_learning

Introduction to Machine Learning Homework Assignments

This repository contains the homework assignments for the "Introduction to Machine Learning" course offered by the Department of Computer Science and Engineering at National Sun Yat-sen University (NSYSU) during the Fall semester of 2023. The assignments cover a wide range of topics, including image processing, data analysis, participation in Kaggle competitions, and building machine learning models.

Repository Structure

The repository is organized into the following directories, each corresponding to a specific homework assignment:

• hw1 - Image Classification
• hw2 - Kaggle Competition and Bike Sharing Demand Prediction
• hw3 - Employee Turnover Prediction and Credit Card Fraud Detection
• hw4 - Polynomial Minimization and CNN for Image Classification
• AI GO Competition - Participation in the "AI GO Competition"

Assignments

HW1: Image Classification

• Objective: Write a Python program to display images and classify them as cats or dogs.
• Tasks:
  1. Display an image based on a user-input number (1-20).
  2. Classify the displayed image as a cat or dog by comparing it against images in ./reference/cats/ and ./reference/dogs/.

HW2: Kaggle Competition and Bike Sharing Demand Prediction

• Objective: Participate in a Kaggle competition and predict bike-sharing demand using linear regression.
• Tasks:
  1. Complete the House Prices Kaggle competition.
  2. Predict bike-sharing demand and evaluate the model's performance.

HW3: Employee Turnover Prediction and Credit Card Fraud Detection

• Objective: Predict employee turnover and detect fraudulent credit card transactions.
• Tasks:
  1. Build and evaluate a logistic regression model for predicting employee turnover.
  2. Detect fraudulent transactions using a decision tree and evaluate the model.

HW4: Polynomial Minimization and CNN for Image Classification

• Objective: Implement functions for polynomial minimization and train a CNN for image classification.
• Tasks:
  1. Write functions to find the minimum value of a given polynomial.
  2. Train a CNN to classify images of cats and dogs.

AI GO Competition

• Objective: Participate in the "AI GO Competition".
• Tasks:
  1. Predict house prices based on provided datasets.
  2. Enhance models using external datasets and submit predictions in the specified format.