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Project45

Data Science 프로젝트 (5주차) A Complete Introduction and Walkthrough (1/2) Machine Learning Modeling Once feature engineering/construction is done, we can get started with the machine learning! All of our data (both training and testing) is aggregated for each household and so can be directly used in a model. To first show the process of modeling, we'll use the capable Random Forest Classifier in Scikit-Learn. This probably.. 2023. 4. 15.
Data Science 프로젝트 (4주차) A Complete Introduction and Walkthrough (1/2) Costa Rican Household Poverty Level Prediction Welcome to another Kaggle challenge! The objective of the Costa Rican Household Poverty Level Prediction contest is to develop a machine learning model that can predict the poverty level of households using both individual and household characteristics. This "data science for good" project offers the opp.. 2023. 4. 8.
Data Science 프로젝트 (3주차) Introduction: Home Credit Default Risk Competition This notebook is intended for those who are new to machine learning competitions or want a gentle introduction to the problem. I purposely avoid jumping into complicated models or joining together lots of data in order to show the basics of how to get started in machine learning! Any comments or suggestions are much appreciated. In this notebook.. 2023. 4. 1.
Data Science 프로젝트 (2주차-2) Interactive Porto Insights - A Plot.ly Tutorial Introduction This competition is hosted by the third largest insurance company in Brazil: Porto Seguro with the task of predicting the probability that a driver will initiate an insurance claim in the next year. This notebook will aim to provide some interactive charts and analysis of the competition data by way of the Python visualisation library .. 2023. 3. 25.

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