This repository contains code and associated files for deploying ML models using AWS SageMaker. This repository consists of a number of tutorial notebooks for various coding exercises, mini-projects, and project files that will be used to supplement the lessons of the Nanodegree.
I'm attempting the NYC Taxi Duration prediction Kaggle challenge. I'll by using a combination of Pandas, Matplotlib, and XGBoost as python libraries to help me understand and analyze the taxi dataset that Kaggle provides. The goal will be to build a predictive model for taxi duration time. I'll also be using Google Colab as my jupyter notebook.…
Demonstrating how to build an XGBoost model and deploy it to Algorithmia, from a Jupyter notebook
This repository contains the notebooks used for the Zindi Challenge to predict the amount of money spent by a tourist in Tanzania using an XGBoost approach
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