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mooc-machine-learning-weather-climate

https://github.com/ecmwf-training/mooc-machine-learning-weather-climate

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
  • ✓
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    Found codemeta.json file
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    .zenodo.json file
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    DOI references
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    Academic publication links
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    1 of 15 committers (6.7%) from academic institutions
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    Scientific vocabulary similarity
    Low similarity (10.2%) to scientific vocabulary
Last synced: 11 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: ecmwf-training
  • License: apache-2.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 33.3 MB
Statistics
  • Stars: 197
  • Watchers: 14
  • Forks: 177
  • Open Issues: 10
  • Releases: 0
Created over 3 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

MOOC Machine Learning in Weather & Climate - Jupyter notebook exercises

This repository hosts the Jupyter notebook based exercises of the Massive Open Online Course (MOOC) on Machine Learning in Weather & Climate, which can now be found on ECMWF's learning platform https://learning.ecmwf.int/.

The notebook files can be found in the subdirectories corresponding to each tier of the MOOC. These include the following:

Tier 1 notebooks (ML in Weather & Climate)

In this tier there is only one notebook that demonstrates how to build a simple neural network on the WeatherBench dataset.

Tier 2 notebooks (Concepts of Machine Learning)

In this tier there are notebooks for each module that provide practical guidance on key concepts of Machine Learning.

Tier 3 notebooks (Practical ML Applications in Weather & Climate)

Each module of this tier contains notebooks that demonstrate practical applications of Machine Learning in the various stages of Numerical Weather and Climate prediction.

How to run the notebooks

The notebooks can either be downloaded and run on participants' own computers, or they can be run directly in various cloud environments. The advantage of the latter is that no software needs to be installed locally. In each notebook a number of options are provided where the notebook can be run. These may include the following:

|Colab|Kaggle|Deepnote| |:-:|:-:|:-:| |Colab|Kaggle|Deepnote| |Colab requires a Google account, which can easily be set-up for free.|Requires (free) registration with Kaggle. Once in, "switch on the internet" via settings.|Requires (free) registration. Deepnote is a good platform also for collaboration.|

License

Unless otherwise stated, the notebooks fall under Apache License 2.0. In applying this licence, ECMWF does not waive the privileges and immunities granted to it by virtue of its status as an intergovernmental organisation nor does it submit to any jurisdiction.

Owner

  • Name: ecmwf-training
  • Login: ecmwf-training
  • Kind: organization

GitHub Events

Total
  • Watch event: 3
  • Issue comment event: 1
  • Fork event: 3
Last Year
  • Watch event: 3
  • Issue comment event: 1
  • Fork event: 3

Committers

Last synced: 11 months ago

All Time
  • Total Commits: 139
  • Total Committers: 15
  • Avg Commits per committer: 9.267
  • Development Distribution Score (DDS): 0.662
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Florian Pinault F****t@e****t 47
Chris Stewart 6****f 33
Mariana Clare m****7@i****k 21
siham garroussi m****g@s****l 13
Mariana Clare 3****7 6
brajard j****d@u****r 6
b8raoult 5****t 3
Jesper Dramsch j****r@d****t 2
gpanegrossi 1****i 2
Marc Bocquet m****t@e****r 1
Matthew Chantry m****y@e****t 1
Virginia Poli v****i@P****t 1
dcasella79 d****l@g****m 1
Jussi Leinonen j****n@m****h 1
Randy Chase r****2@R****l 1
Committer Domains (Top 20 + Academic)
ecmwf.int: 2 meteoswiss.ch: 1 poli-lp-smr.smr.arpa.emr.net: 1 enpc.fr: 1 dramsch.net: 1 upmc.fr: 1 ic.ac.uk: 1

Issues and Pull Requests

Last synced: 11 months ago

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  • Pull requests: 0
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Dependencies

.github/workflows/test-notebooks.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
tests/requirements_tests.txt pypi
  • ipykernel * test
  • nbconvert * test
  • nbformat * test
  • pytest * test
tier_2/data_handling/climetlab-my-plugin-solution/requirements.txt pypi
  • climetlab *
tier_2/data_handling/climetlab-my-plugin-solution/requirements_dev.txt pypi
  • black * development
  • flake8 * development
  • isort * development
tier_2/data_handling/climetlab-my-plugin-solution/setup.py pypi
  • climetlab >=0.10.0
tier_2/data_handling/climetlab-my-plugin-solution/tests/requirements_tests.txt pypi
  • ipykernel * test
  • nbconvert * test
  • nbformat * test
  • pytest * test
tier_2/deep_learning/requirements-pytorch.txt pypi
  • climetlab-mltc-surface-observation-postprocessing >=0.3.0
  • matplotlib *
  • numpy *
  • pytorch-lightning *
  • scikit-learn *
  • torch *
tier_2/deep_learning/requirements-tensorflow.txt pypi
  • climetlab-mltc-surface-observation-postprocessing >=0.3.0
  • matplotlib *
  • numpy *
  • scikit-learn *
  • tensorflow *
tier_3/ocean_climate/e3ci/requirements.txt pypi
  • folium *
  • geopandas *
  • mapclassify *
  • matplotlib *
  • numpy *
  • openpyxl *
  • pandas *
  • sklearn *
  • tqdm *
  • tslearn *
tier_1/environment.yml conda
  • numpy
  • tensorflow
  • xarray
tier_3/data_assimilation/environment.yaml conda
  • ca-certificates
  • certifi
  • ipywidgets
  • jupyterlab
  • matplotlib
  • numpy
  • openssl
  • pydot
  • scikit-learn
  • seaborn
  • tensorflow
  • tqdm
tier_3/observations/environment.yml conda
  • _py-xgboost-mutex 2.0
  • appdirs 1.4.4
  • appnope 0.1.2
  • asttokens 2.0.5
  • atk-1.0 2.38.0
  • backcall 0.2.0
  • brotli 1.0.9
  • brotli-bin 1.0.9
  • brotlipy 0.7.0
  • bzip2 1.0.8
  • ca-certificates 2023.01.10
  • cairo 1.16.0
  • catboost 1.1.1
  • cctools_osx-64 973.0.1
  • certifi 2022.12.7
  • cffi 1.15.1
  • charset-normalizer 2.1.1
  • clang 13.0.1
  • clang-13 13.0.1
  • clang_osx-64 13.0.1
  • clangxx 13.0.1
  • clangxx_osx-64 13.0.1
  • cloudpickle 2.2.1
  • cmdstan 2.29.2
  • cmdstanpy 1.1.0
  • colorama 0.4.6
  • comm 0.1.2
  • compiler-rt 13.0.1
  • compiler-rt_osx-64 13.0.1
  • contourpy 1.0.7
  • convertdate 2.4.0
  • cryptography 39.0.0
  • cycler 0.11.0
  • cython 0.29.33
  • debugpy 1.5.1
  • decorator 5.1.1
  • entrypoints 0.4
  • ephem 4.1.4
  • executing 0.8.3
  • expat 2.5.0
  • font-ttf-dejavu-sans-mono 2.37
  • font-ttf-inconsolata 3.000
  • font-ttf-source-code-pro 2.038
  • font-ttf-ubuntu 0.83
  • fontconfig 2.14.2
  • fonts-conda-ecosystem 1
  • fonts-conda-forge 1
  • fonttools 4.38.0
  • freetype 2.12.1
  • fribidi 1.0.10
  • fsspec 2023.1.0
  • gdk-pixbuf 2.42.10
  • gettext 0.21.1
  • giflib 5.2.1
  • graphite2 1.3.13
  • graphviz 7.1.0
  • gtk2 2.24.33
  • gts 0.7.6
  • harfbuzz 6.0.0
  • hijri-converter 2.2.4
  • holidays 0.19
  • icu 70.1
  • idna 3.4
  • ipykernel 6.19.2
  • ipython 8.8.0
  • jedi 0.18.1
  • joblib 1.2.0
  • jpeg 9e
  • jupyter_client 7.4.8
  • jupyter_core 5.1.1
  • kiwisolver 1.4.4
  • korean_lunar_calendar 0.3.1
  • lcms2 2.14
  • ld64_osx-64 609
  • lerc 4.0.0
  • libblas 3.9.0
  • libbrotlicommon 1.0.9
  • libbrotlidec 1.0.9
  • libbrotlienc 1.0.9
  • libcblas 3.9.0
  • libclang-cpp13 13.0.1
  • libcxx 14.0.6
  • libdeflate 1.17
  • libffi 3.4.2
  • libgd 2.3.3
  • libgfortran 5.0.0
  • libgfortran5 11.3.0
  • libglib 2.74.1
  • libiconv 1.17
  • libjpeg-turbo 2.1.4
  • liblapack 3.9.0
  • libllvm11 11.1.0
  • libllvm13 13.0.1
  • libllvm14 14.0.6
  • libopenblas 0.3.21
  • libpng 1.6.39
  • libprotobuf 3.21.12
  • librsvg 2.54.4
  • libsodium 1.0.18
  • libsqlite 3.40.0
  • libtiff 4.5.0
  • libtool 2.4.7
  • libwebp 1.2.4
  • libwebp-base 1.2.4
  • libxcb 1.13
  • libxgboost 1.7.1
  • libxml2 2.10.3
  • libzlib 1.2.13
  • lightgbm 3.3.5
  • lightning-utilities 0.6.0.post0
  • llvm-openmp 15.0.7
  • llvm-tools 13.0.1
  • llvmlite 0.39.1
  • lunarcalendar 0.0.9
  • make 4.3
  • matplotlib-base 3.6.3
  • matplotlib-inline 0.1.6
  • mkl 2022.2.1
  • munkres 1.1.4
  • ncurses 6.3
  • nest-asyncio 1.5.6
  • nfoursid 1.0.1
  • ninja 1.11.0
  • numba 0.56.4
  • numpy 1.23.5
  • openjpeg 2.5.0
  • openssl 3.0.7
  • packaging 23.0
  • pandas 1.5.3
  • pango 1.50.12
  • parso 0.8.3
  • patsy 0.5.3
  • pcre2 10.40
  • pexpect 4.8.0
  • pickleshare 0.7.5
  • pillow 9.4.0
  • pip 23.0
  • pixman 0.40.0
  • platformdirs 2.5.2
  • plotly 5.13.0
  • pmdarima 2.0.2
  • pooch 1.6.0
  • prompt-toolkit 3.0.36
  • prophet 1.1.2
  • psutil 5.9.0
  • pthread-stubs 0.4
  • ptyprocess 0.7.0
  • pure_eval 0.2.2
  • py-xgboost 1.7.1
  • pycparser 2.21
  • pygments 2.11.2
  • pymeeus 0.5.12
  • pyod 1.0.7
  • pyopenssl 23.0.0
  • pyparsing 3.0.9
  • pysocks 1.7.1
  • python 3.10.8
  • python-dateutil 2.8.2
  • python-graphviz 0.20.1
  • python_abi 3.10
  • pytorch 1.13.1
  • pytorch-lightning 1.9.0
  • pytz 2022.7.1
  • pyyaml 6.0
  • pyzmq 23.2.0
  • readline 8.1.2
  • requests 2.28.2
  • scikit-learn 1.2.1
  • scipy 1.10.0
  • setuptools 66.1.1
  • shap 0.41.0
  • sigtool 0.1.3
  • six 1.16.0
  • sleef 3.5.1
  • slicer 0.0.7
  • stack_data 0.2.0
  • statsforecast 1.4.0
  • statsmodels 0.13.5
  • tapi 1100.0.11
  • tbats 1.1.1
  • tbb 2021.7.0
  • tbb-devel 2021.7.0
  • tenacity 8.1.0
  • threadpoolctl 3.1.0
  • tk 8.6.12
  • torchmetrics 0.11.1
  • tornado 6.2
  • tqdm 4.64.1
  • traitlets 5.7.1
  • typing-extensions 4.4.0
  • typing_extensions 4.4.0
  • tzdata 2022g
  • u8darts 0.23.1
  • u8darts-all 0.23.1
  • unicodedata2 15.0.0
  • urllib3 1.26.14
  • wcwidth 0.2.5
  • wheel 0.38.4
  • xarray 2023.1.0
  • xgboost 1.7.1
  • xorg-libxau 1.0.9
  • xorg-libxdmcp 1.1.3
  • xz 5.2.6
  • yaml 0.2.5
  • zeromq 4.3.4
  • zlib 1.2.13
  • zstd 1.5.2
tier_3/ocean_climate/unsupervised_ml_ocean/environment.yml conda
  • cartopy
  • conda
  • matplotlib
  • numpy
  • scikit-learn
  • scipy
  • seaborn