CSST 104: Advanced Machine Learning

Welcome to the repository for CSST 104: Advanced Machine Learning! This repository compiles various works, exercises, assessments, and resources related to the course.

Personal Information

Name: Renz Dexter M. Perci
Section: BSCS 3A
Course: CSST 104
Department: College of Computer Studies
School: Laguna State Polytechnic University - Santa Cruz (Main) Campus
Professor: Mark P. Bernardino, MSCS

Table of Contents

• Welcome
• Personal Information
• Introduction
• Course Description
• Codes

Introduction

This repository serves as a comprehensive collection of materials for CSST 104: Advanced Machine Learning. Here, you will find exercises, assessments, projects, and other resources to aid your learning journey in this subject.

Course Description

A broad range of statistical and machine learning techniques will be introduced to students in this course. They will become acquainted with data analysis and the instruments required to realistically examine the many dimensions of datasets.

Codes

Exercises

• Github Links:
  • Basic Data Analysis on Sales Data 2 Datasets
  • Exploratory Data Analysis on Synthetic Student Performance Dataset
  • Linear Regression on Synthetic Dataset
  • Multiple Linear Regression on Synthetic Dataset
  • Logistic Regression on Students Performance Dataset
  • Time Series Analysis Using ARIMA on Sales of Shampoo over a Three Year Period Dataset
• Google Colab Links:
  • Basic Data Analysis on Sales Data 2 Datasets
  • Exploratory Data Analysis on Synthetic Student Performance Dataset
  • Linear Regression on Synthetic Dataset
  • Multiple Linear Regression on Synthetic Dataset
  • Logistic Regression on Students Performance Dataset
  • Time Series Analysis Using ARIMA on Sales of Shampoo over a Three Year Period Dataset

Assessment Tasks

• Github Links:
  • Exploratory Data Analysis of Product Data
  • Linear Regression on Lesson 4 Student Grades Dataset
  • Multiple Linear Regression on Lesson 4 Student Grades Dataset
  • Logistic Regression on Bank Customer Dataset
  • Predicting Feedback on Online Food Orders Using Logistic Regression
  • Netflix Userbase Analysis
  • Pollution Data Time Series Analysis Using ARIMA
• Google Colab Links:
  • Exploratory Data Analysis of Product Data
  • Linear Regression on Lesson 4 Student Grades Dataset
  • Multiple Linear Regression on Lesson 4 Student Grades Dataset
  • Logistic Regression on Bank Customer Dataset
  • Predicting Feedback on Online Food Orders Using Logistic Regression
  • Netflix Userbase Analysis
  • Pollution Data Time Series Analysis Using ARIMA

Midterm

• Github Links:
  • Forecasting with ARIMA Model
• Google Colab Links:
  • Forecasting with ARIMA Model

Notes

• Github Links:
  • Basics of Data Analysis
  • Time Series Analysis
• Google Colab Links:
  • Basics of Data Analysis
  • Time Series Analysis