A simple and lightweight data engineering template using Apache Airflow and Metabase

This project aims to predict the salary of employees based on their years of experience using supervised machine learning techniques.

End-to-end Weather ETL built with Apache Airflow, MinIO, and PostgreSQL. Extract Open-Meteo hourly data → normalize to Parquet → load to L1/L2 tables with idempotent, backfillable DAGs, simple data checks, and SQL-only transformations.

This project focuses on processing the Iris Plants dataset using the Random Forest algorithm in machine learning, where various features of iris flowers are analyzed to explore patterns and relationships within the data.

Background problem Pada proyek ini, saya melakukan klasifikasi dataset Iris menggunakan algoritma K-Nearest Neighbors (KNN).

Superstore is a business that offers a wide range of products in several regions mainly in the United States, with key categories such as furniture, technology, and office supplies. The data used in this analysis was obtained from Kaggle.com

Exploratory Data Analysis (EDA) adalah proses awal dalam analisis data yang bertujuan untuk memahami struktur data, menemukan pola, mendeteksi anomali, menguji asumsi, dan mencari hubungan antar variabel sebelum melakukan pemodelan lebih lanjut.

Proyek ini bertujuan untuk melakukan klasifikasi pada dataset Breast Cancer menggunakan algoritma Random Forest. Dataset yang digunakan berasal dari scikit-learn.

Tugas Portofolio Dibimbing Digital Skill Fair 32- Data Science oleh Rosida Dewi Utami #Dibimbing #DigitalSkillFair32