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derbuhlert's Projects

bike_predict icon bike_predict

A demo of an end-to-end machine learning pipeline, using RStudio Connect

databook_python icon databook_python

IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz

databookuw.jl icon databookuw.jl

Julia Pluto notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz

datascience icon datascience

Data Science in Julia course for JuliaAcademy.com, taught by Huda Nassar

db-dashboard icon db-dashboard

Project files of the article featured here: http://db.rstudio.com/best-practices/dashboards/

fastest-lap icon fastest-lap

Fastest-lap is a vehicle dynamics simulator. It can be used to understand vehicle dynamics, to learn about driving techniques, to design car prototypes, or just for fun!

house-price-prediction-using-flask icon house-price-prediction-using-flask

Model deployment with flask api, using Linear Regression to predict the price value. Deploy ML Models Using Flask to take your models from python to production.

jarvis2 icon jarvis2

Awesome dashboard built with Flask and Mithril

mml-companion icon mml-companion

This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Faisal and Cheng Ong, written in python for Jupyter Notebook.

plane-notify icon plane-notify

Notify If a selected plane has taken off or landed using OpenSky or ADS-B Exchange data. Compares older data to newer data to determine if a landing or takeoff has occurred. As well as nav modes, emergency squawk and resolution advisory notifications. Can output to Twitter, Discord, and Pushbullet

prml icon prml

PRML algorithms implemented in Python

tc icon tc

A command-line twitter client with smart filtering and statistical classification

vmls-companions icon vmls-companions

These are companion notebooks written in Julia and Python for: "Introduction to Applied Linear Algebra" by Boyd and Vandenberghe.

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