Tags: Jupyter notebooks

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  1. Refractory Complex Concentrated Alloy Melting Point Calculation

    28 May 2020 | | Contributor(s):: Zachary D McClure, Saaketh Desai, Alejandro Strachan

    Calculate melting point of BCC-type high entropy alloys through phase coexistence method

  2. Jon Nykiel

    I'm Jon Nykiel, a fourth year undergraduate studying Materials Science and Applied Physics at the Ohio State University. I'm participating in NCN's SCALE URE program with Dr. Strachan of Purdue...

    https://nanohub.org/members/288810

  3. Test Tool for Neural Network Reactive Force Field for CHNO systems

    14 May 2020 | | Contributor(s):: Pilsun Yoo, Saaketh Desai, Michael N Sakano, Peilin Liao, Alejandro Strachan

    Run molecular dynamics and Do testing using the neural network reactive force field for nitramines

  4. PhysiBoSSa: cell fate decision in TNF Boolean model

    13 May 2020 | | Contributor(s):: Gerard Pradas, Arnau Montagud, Miguel Ponce de Leon

    PhysiBoSSa model of the cell fate decision in TNF Boolean model in a multicellular multiscale system

  5. XRD interactive trends plot

    11 May 2020 | | Contributor(s):: Enze Chen

    Observe changes in powder XRD spectra by modifying experimental parameters.

  6. Running a Python 3 Script in a nanoHUB Jupyter Notebook

    01 May 2020 | | Contributor(s):: Tanya Faltens

    This tutorial will show you how to create and run Python 3 code in a Jupyter notebook, rather than creating and running a Python script. We are working along with Chapter 1.8 “Writing a program” in the Python for Everybody course. In this lesson they execute a Python script that...

  7. Hands-on Unsupervised Learning using Dimensionality Reduction via Matrix Decomposition (2nd offering)

    30 Apr 2020 | | Contributor(s):: Michael N Sakano, Alejandro Strachan

    This tutorial introduces unsupervised machine learning algorithms through dimensionality reduction via matrix decomposition techniques in the context of chemical decomposition of reactive materials in a Jupyter notebook on nanoHUB.org. The tool used in this demonstration...

  8. Hands-on Supervised Learning: Part 2 - Classification and Random Forests (2nd offering)

    30 Apr 2020 | | Contributor(s):: Saaketh Desai

    This tutorial introduces neural networks for classification tasks and random forests for regression tasks via Jupyter notebooks on nanoHUB.org. You will learn how to create and train a neural network to perform a classification, as well as how to define and train random forests. The tools used...

  9. Hands-on Unsupervised Learning using Dimensionality Reduction via Matrix Decomposition (1st offering)

    29 Apr 2020 | | Contributor(s):: Michael N Sakano, Alejandro Strachan

    This tutorial introduces unsupervised machine learning algorithms through dimensionality reduction via matrix decomposition techniques in the context of chemical decomposition of reactive materials in a Jupyter notebook on nanoHUB.org. The tool used in this demonstration...

  10. Hands-on Supervised Learning: Part 2 - Classification and Random Forests (1st offering)

    24 Apr 2020 | | Contributor(s):: Saaketh Desai

    This tutorial introduces neural networks for classification tasks and random forests for regression tasks via Jupyter notebooks on nanoHUB.org. You will learn how to create and train a neural network to perform a classification, as well as how to define and train random forests. The tools used...

  11. Hands-on Supervised Learning: Part 1 - Linear Regression and Neural Networks

    22 Apr 2020 | | Contributor(s):: Saaketh Desai

    This tutorial introduces supervised learning via Jupyter notebooks on nanoHUB.org. You will learn how to setup a basic linear regression in a Jupyter notebook and then create and train a neural network. The tool used in this demonstration is Machine Learning for Materials Science:...

  12. Repositories and Data Management (2nd offering)

    22 Apr 2020 | | Contributor(s):: Zachary D McClure, Alejandro Strachan

    This tutorial introduces database infrastructure and APIs for performing different scales of querying. You will learn how to access different suites of information from three prominent databases, and some advanced examples of data visualization and processing will be discussed. The Querying Data...

  13. Repositories and Data Management (1st offering)

    21 Apr 2020 | | Contributor(s):: Zachary D McClure, Alejandro Strachan

    This tutorial introduces database infrastructure and APIs for performing different scales of querying. You will learn how to access different suites of information from three prominent databases, and some advanced examples of data visualization and processing will be discussed. The Querying Data...

  14. Introduction to Jupyter Notebooks, Data Organization and Plotting (1st offering)

    21 Apr 2020 | | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan

    This tutorial gives an introductory demonstration of how to create and use Jupyter notebooks. It showcases the libraries Pandas to manipulate and organize data with functionalities similar to those of Excel on python, and Plotly, a library used to create interactive plots for enhanced...

  15. Introduction to Jupyter Notebooks, Data Organization and Plotting (2nd offering)

    21 Apr 2020 | | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan

    This tutorial gives an introductory demonstration of how to create and use Jupyter notebooks. It showcases the libraries Pandas to manipulate and organize data with functionalities similar to those of Excel on python, and Plotly, a library used to create interactive plots for enhanced...

  16. PhysiBoSSa Simulation with ECM

    20 Apr 2020 | | Contributor(s):: Marco Ruscone, Vincent Noel, Laurence Calzone, Gaelle Letort, Arnau Montagud

    Agent based multicellular simulation with extracellular matrix interaction

  17. Setting up Your nanoHUB File Structure in Jupyter Notebooks

    17 Apr 2020 | | Contributor(s):: Tanya Faltens

    This tutorial takes you through the steps to set up your nanoHUB file structure in Jupyter Notebooks.Be sure to get a copy of the pdf that accompanies the video instructions by clicking on the Supporting Docs tab for this resource.

  18. Unsupervised learning using dimensionality reduction via matrix decomposition

    14 Apr 2020 | | Contributor(s):: Michael N Sakano, Alejandro Strachan

    Learn PCA and NMF via chemistry example

  19. A virion infected-cell response tissue simulator

    13 Apr 2020 | | Contributor(s):: Yafei Wang, Randy Heiland, Paul Macklin

    Simulate infected cell response to virus with PhysiCell

  20. A virion replication tissue simulator

    13 Apr 2020 | | Contributor(s):: Yafei Wang, Randy Heiland, Paul Macklin

    Simulate virus replication dynamics with PhysiCell