⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

The fastai book, published as Jupyter Notebooks

This repository contains implementations and illustrative code to accompany DeepMind publications

Practice your pandas skills!

The goal of CLAIMED is to enable low-code/no-code rapid prototyping style programming to seamlessly CI/CD into production.

Classical Aerodynamics of potential flow using Python and Jupyter Notebooks

Digital Signal Processing - Theory and Computational Examples

Examples of how to use machine learning algorithms in computational fluid dynamics.

Whole building non-residential hourly energy meter data from the Great Energy Predictor III competition

Time Series Analysis using LSTM for Wind Energy Prediction.

Notes on Scientific Computing for Biomechanics and Motor Control

This is a repository to gather the teaching material used for the course Python for Wind Energy organised at DTU Wind Energy

IEA Task 43: pre-construction energy estimate data standard repository

We extract actual SCADA data of a certain offshore wind farm and artificially remove some of the data, including but not limited to deleting all data of a certain time period, data of a certain tur…

Marine Hydrodynamics

Predict Energy Output of a wind turbine at any geo-coordinate for a time-series of next 72 hours using ML and live weather forecast details. Developed an Android App in Flutter framework and Flask …

Data Science in Wind Resource Assessment Tutorial at PyData San Diego, March 2020

Bayesian statistical modelling using numpy and PyMC3. Telling stories using the language of probability. And more!

Code for "Conditional Variational Autoencoders for Probabilistic Wind Turbine Blade Fatigue Estimation using SCADA data"

Lecture notes on sensors and actuators using ipython notebooks.

Repository for Parallel Python @ ASPP 2019

Diurnal Cycles Benchmark: a large domain in complex terrain

Data analysis for wind turbine power generator data

Brief data analysis on EU Wind Energy Potential 30 years of records.

The 3rd edition of course.fast.ai