Data Science Use Cases

Welcome to my Data Science repository! This repository contains self-made projects, scripts, and SQL queries showcasing my understanding and ability to tackle case studies with a data science approach. I have categorized various concepts of practice into separate directories. Feel free to look around!

Introduction

Hi Everyone! My name is Sang Putu, and I am a Data Science Enthusiast. I work as a Data Analyst (also with Data Scientist responsibilities) in a Pharmaceutical Company. My work areas include Marketing Analytics, Market Research & Insights, Product Portfolio, and Supply Chain Management. I enjoy using my knowledge to help people, which inspired me to create this repository. I will try to update this repo in my free time.

Directories

Classification

Description: This directory focuses on classification tasks with several datasets. In the future, it might be moved to the Predictions directory.

Classification Projects

Clustering

Description: This directory focuses on clustering tasks with various datasets. In the future, it might be moved to the Predictions directory.

Clustering Projects

Predictions

Description: This directory focuses on predicting values or labels for each dataset using algorithms such as Regressions, SVM, and Random Forest. Some projects involve data cleaning and exploratory data analysis (EDA), while others use pre-cleaned data.

Predictions Projects

SQL

Description: This directory focuses on using SQL to create database systems and perform data querying, with examples of DDL and DML. Most databases are dummy data created by myself and are free to reproduce.

SQL Projects

Scripts

Description: This directory serves as a cloud for my Python scripts, which can be loaded as modules for tasks such as visualizations and dataframe processing.

VBA

Description: With experience in using Microsoft Excel, some tasks become tedious. I have uploaded VBA scripts to be used as macros on your own devices.

VBA Projects

  • Text Similarity
Description
A repository of Data Science Principles' demonstration of workflows and how to's in analyzing datasets.
Readme 5.9 MiB
Languages
Jupyter Notebook 97%
Python 2.8%
Visual Basic 6.0 0.2%