AWS SageMaker Lab 3.4 | Training a Machine Learning Model
Автор: Mehmet Akif Köz
Загружено: 2024-03-14
Просмотров: 924
Описание:
🔍 Lab overview
In this lab, I will continue exploring the biomechanical vertebral column dataset. I will first split the dataset into three separate datasets for training, validation, and testing. I will then use this data to train a machine learning (MML) model by using the XGBoost algorithm.
📊 Dataset Link: Vertebral Column Dataset
https://archive.ics.uci.edu/dataset/2...
🎯 Objectives
In this lab, I have:
• Split data into training, validation and test datasets
• Train a XGBoost model in Amazon SageMaker
🛠️ Prerequisites
This lab requires:
• Access to a notebook computer with Wi-Fi and Microsoft Windows, macOS, or Linux (Ubuntu, SUSE, or Red Hat)
• For Microsoft Windows users: Administrator access to the computer
• An internet browser such as Chrome, Firefox, or IE9 (previous versions of Internet Explorer are not supported)
🕒 Duration
• This lab requires 30 minutes to complete. The lab will remain active for 120 minutes
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#AmazonSageMaker
#DataScience
#MachineLearning
#VertebralColumnDataset
#XGBoost
#TrainingData
#ValidationData
#TestingData
#ModelTraining
#BiomechanicalData
#DataSplitting
#XGBoostAlgorithm
#AWSMachineLearning
#DataPreprocessing
#ModelEvaluation
#DataAnalysis
#AWSLearning
#MachineLearningModel
#SageMakerLab
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