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2020_force_lithology_prediction

advanced-forecasting-python

Source Code for 'Advanced Forecasting with Python' by Joos Korstanje

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

aermetfromnarr

Python script to create an AERMET file from NARR data if observations are not available.

aermod_framework

This framework creates an easy interface for running AERMOD simulations. This framework will write the input file, run AERMOD, and process the outputs into an excel spreadsheet or into a contour plot using AERPLOT

ai-feynman

anuga_core

AnuGA for the simulation of the shallow water equation

arduino_tensorflowlite_esp32

Allows you to run machine learning models locally on your ESP32 device.

belajar-dart-async

Belajar Dart Async

belajar-dart-collection

Belajar Dart Collection

belajar-dart-dasar

Belajar Pemrograman Dart Dasar

belajar-dart-generic

Belajar Dart Generic

belajar-dart-oop

Belajar Dart Object Oriented Programming

belajar-dart-unit-test

Belajar Dart Unit Test

belajar-git

Tutorial Git dalam Bahasa Indonesia

belajar_dart_library

Belajar Dart Library

benchmark_funwave

Benchmark tests for FUNWAVE-TVD

buckinghampy

Python code that implement the Buckingham-Pi theorem for different variables and return all possible dimensionless pi terms

building-statistical-models-in-python

Building Statistical Models in Python, Published by Packt

caline4

R interface to CALINE4 dispersion model

celeris

climpred

:earth_americas: Verification of weather and climate forecasts :earth_africa:

cn-stream

Computation of nonlinear regular ocean waves using stream function

cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization.

coastal-forecast

Web-based application to host a trained coastal forecast machine learning model.

coastal_models_python

iPython notebooks describing models of coastal processes and systems

coastlib

Coastal engineering library and tools

dall-e-explained

Description and applications of OpenAI's paper about DALL-E (2021) and implementation of other (CLIP-guided) zero-shot text-to-image generation schemes

dash-sample-apps

Open-source demos hosted on Dash Gallery

deep-learning

Deep learning related experimental projects