This project exemplifies deploying a multi-class classifier model using Random Forest on AWS SageMaker to predict mobile phone price ranges. The repository contains the necessary code and dataset.
The goal of this project was to develop and deploy a Random Forest multi-class classifier model on AWS SageMaker for predicting mobile phone price ranges.
- VS Code
- Anaconda
- AWS SageMaker
- AWS S3
- AWS IAM
sagemaker-custom-script.ipynb
: Jupyter Notebook containing the project implementation.script.py
: Python script used for training the model.requirements.txt
: File listing required packages for the project.mob_price_classification_train.csv
: Dataset used for model training.train-V-1.csv
andtest-V-1.csv
: Training and testing data files.
To install necessary packages, execute the following command:
pip install -r requirements.txt
This project illustrates the deployment of a machine learning model on AWS SageMaker, underscoring the significance of deploying models in real-world scenarios. For a detailed guide, refer to the provided notebook.
References:
- Video Tutorial: “Implementing an End-to-end Machine Learning Project Using AWS SageMaker” (Duration: 3 hours)