How to train, deploy and monitor a XGBoost regression model in Amazon SageMaker and alert using AWS Lambda and Amazon SNS. SageMaker's Model Monitor will be used to monitor data quality drift using the Data Quality Monitor and regression metrics like MAE, MSE, RMSE and R2 using the Model Quality Monitor.

California house price prediction is done in this notebook

How to train a XGBoost regression model on Amazon SageMaker, host inference on a Docker container running on Amazon ECS on AWS Fargate and optionally expose as an API with Amazon API Gateway.

How to train a XGBoost regression model on Amazon SageMaker, host inference on a serverless function in AWS Lambda and optionally expose as an API with Amazon API Gateway

This is an educational workthrough project from the book "Hands-On ML with Scikit-Learn, Keras and TensorFlow" by Aurélien Géron. It is based on the well-known "California Housing Prices" dataset - through feature engineering I successfully improved the performance of the model used in the book.

California housing price prediction with NN, Random Forest and Linear Regression

How to train a XGBoost regression model on Amazon SageMaker and host inference as an API on a Docker container running on AWS App Runner.

This project is full scale end to end Machine learning project that used to predict the price of the california housing dataset

Predicting California Housing Prices using Decision Tree Regressor

ML, NN, NLP, ARIMA, clustering, classification, mapping

This repository contains a machine learning algorithm that trains a model to predict house prices based on specified features of the homes, using the California Housing Dataset.

This repository contains a machine learning algorithm that trains a Random Forest model to predict house prices based on specified features of the homes, using the California Housing Dataset. The dataset used to train and evaluate the Random Forest model to predict median housing prices.

Pattern Recognition assignment

Build as part of "Building Your First scikit-learn Solution" Pluralsight course.

Get started with Tensorflow/Keras API.

Introduction to Machine Learning using data from the california_housing dataset.

This contains all the project in which i have used Simple Linear Regression to Predict output

Create a platform that will predict a house price based on a user-input zip code and house type