A simple and lightweight data engineering template using Apache Airflow and Metabase
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Updated
May 22, 2024 - Shell
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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.
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.
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
Tugas Portofolio Dibimbing Digital Skill Fair 32- Data Science oleh Rosida Dewi Utami #Dibimbing #DigitalSkillFair32
Proyek ini bertujuan untuk melakukan klasifikasi pada dataset Breast Cancer menggunakan algoritma Random Forest. Dataset yang digunakan berasal dari scikit-learn.
Background problem Pada proyek ini, saya melakukan klasifikasi dataset Iris menggunakan algoritma K-Nearest Neighbors (KNN).
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