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Notebook","category":"Sustainable Development","sub_category":"Education","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"# ARSET Fundamentals of Machine Learning (ML) for Earth Science\n\nMaterials for [ARSET Fundamentals of Machine Learning for Earth Science](https://appliedsciences.nasa.gov/join-mission/training/english/arset-fundamentals-machine-learning-earth-science). This repository contains materials for Session 1, 2, and 3.\n\n## Assignments\n\nThe assignments listed for each session are practice assignments with questions that will be included in the final assignment after Session 3 conclusion.\nThe final assignment will be through a Google Form where you will be answering a set of questions from each one of the Sessions.\n\n## Session 1 Materials:\n\n| Lecture Topic | Interactive Link | \n|---|---|\n| **ML Algorithms Introduction** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NASAARSET/ARSET_ML_Fundamentals/blob/main/session1/1-ML-Algorithms-Introduction-Session1.ipynb) |\n| **Assignment Session 1** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NASAARSET/ARSET_ML_Fundamentals/blob/main/session1/Assignment-Session1.ipynb) |\n\n## Session 2 Materials:\n\n| Lecture Topic | Interactive Link | \n|---|---|\n| **MODIS EDA** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NASAARSET/ARSET_ML_Fundamentals/blob/main/session2/1_MODIS_EDA_Session2.ipynb) |\n| **MODIS Train \u0026 Eval** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NASAARSET/ARSET_ML_Fundamentals/blob/main/session2/2_MODIS_Train_Eval_Session2.ipynb) |\n| **Assignment Session 2** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NASAARSET/ARSET_ML_Fundamentals/blob/main/session2/Assignment-Session2.ipynb) |\n\n## Session 3 Materials:\n\n| Lecture Topic | Interactive Link | \n|---|---|\n| **MODIS Model Tuning** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NASAARSET/ARSET_ML_Fundamentals/blob/main/session3/1-MODIS-Tuning-Session3.ipynb) |\n| **MODIS Explainability** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NASAARSET/ARSET_ML_Fundamentals/blob/main/session3/2-MODIS-Explainability-Session3.ipynb) |\n| **MODIS AutoML** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NASAARSET/ARSET_ML_Fundamentals/blob/main/session3/3-MODIS-AutoML-Session3.ipynb) |\n| **Assignment Session 3** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NASAARSET/ARSET_ML_Fundamentals/blob/main/session3/Assignment-Session3.ipynb) |\n\n## Additional Resources\n\nThe NASA ASTG provides additional introductory materials related to Python and \ndata science in general. You can access some of this interactive material directly from their repository [NASA ASTG py_materials](https://github.com/astg606/py_materials) or under the links below.\n\n### [Installing the Anaconda Python Distribution](#)\n\nIt is not required to have a Python distribution installed on your local machine.\nHowever, we believe that it is important to have one in order to write and run your own Python\napplications. We recommend that you install\nthe Anaconda Python distribution by following the instructions at: [Anconda installation Guide](https://docs.continuum.io/anaconda/install/)\n\n### [Installing Git](#)\n\nTo install Git on your local machine, follow the installation instructions: [Getting Started - Installing Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)\n\nTo fully follow all the topics below, you need to have a **gmail** account in order to access Google Colaboratory. Each course will be taught through the Google cloud based Jupyter notebook.\n\n### \u003cspan style=\"color: red\"\u003eStarting Point\u003c/span\u003e\n\n| Lecture Topic | Interactive Link |\n|---|---|\n| **Introduction to Jupyter Notebook**  | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/jupyter_notebook/jupyter_notebook_introduction.ipynb) |\n| **Introduction to Git**  | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/git_tutorial/basic_git_tutorial.ipynb) |\n\n### \u003cspan style=\"color: red\"\u003eIntroduction to Python\u003c/span\u003e\n\nIf you have never been exposed to Python, you need to take this Introduction to Python course.  In case you did some Python programming in the past and you want to assess your Python knowledge, take the following test (in less that 15 minutes and without using any help):\n\n\u003ccenter\u003e\n\u003ca href=\"https://forms.gle/PTV6xFCA21NYkqfp9\"\u003ePython Assessment Test\u003c/a\u003e\n\u003c/center\u003e\n\nIf you score at least 80% then only take the **I/O on Text Files** topic. Otherwise, take the entire course.\n\n| Lecture Topic | Interactive Link | \n|---|---|\n| **Running Python**  | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/welcome/running_python.ipynb) |\n| **Data Types**  | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/data_types/python_data_types.ipynb) |\n| **Conditional Statements**  | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/conditional_logic/introduction_conditionals.ipynb) | \n| **Loops** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/loops/introduction_loops.ipynb) | \n| **Advanced Data Types** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/data_types/python_data_structures.ipynb) |\n| **Functions** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/functions_modules/introduction_functions.ipynb) | \n| **Modules** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/functions_modules/introduction_modules.ipynb) | \n| **I/O on Text Files** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/input_output/introduction_io_text_files.ipynb) | \n\n| Lecture Topic | Interactive Link | \n|---|---|\n| **Introduction to Turtle** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JulesKouatchou/py_data_science/blob/master/introduction_turtle.ipynb) |\n| **A place to run the code** | [https://repl.it/](https://repl.it/) |\n\n### \u003cspan style=\"color: red\"\u003eData Science Tools\u003c/span\u003e\n\n| Lecture Topic | Interactive Link | \n|---|---|\n| **Introduction to Numpy** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/numpy/introduction_numpy.ipynb) |\n| **Basic Visualization with Matplotlib** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/visualization/introduction_matplotlib.ipynb) |\n| **Introduction to Pandas** | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/astg606/py_materials/blob/master/pandas/introduction_pandas.ipynb) |\n\n## Additional References\n\n- [awesome-earth-artificial-intelligence](https://github.com/ESIPFed/Awesome-Earth-Artificial-Intelligence)\n- [awesome-open-geoscience](https://github.com/softwareunderground/awesome-open-geoscience)\n- [segment-anything-geospatial](https://github.com/opengeos/segment-geospatial)\n\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/308103","html_url":"https://ost.ecosyste.ms/projects/308103"}