All Categories (1-10 of 10)

1. 

   Ufoma Silas Anamu

   https://nanohub.org/members/407195

2. Adaptive Experimentation for Science: A More Efficient Version of Design of Experiments

   Teaching Materials | 05 Jan 2023 | Contributor(s):: Sterling Baird, Taylor Sparks

   GitHub Jupyter notebook tutorials: https://github.com/sparks-baird/self-driving-lab-demo/tree/main/notebooks/escience YouTube guided walkthroughs: https://youtu.be/Evua529dAgc

3. Learning and Teaching Data Science using nanoHUB’s Cloud Resources

   Online Presentations | 18 Mar 2022 | Contributor(s):: Alejandro Strachan

   This talk will discuss how data science is accelerating innovation in STEM fields. These tools enable the efficient handling of valuable data, the identification of patterns in large data collections, the development of predictive models, and the optimal design of experiments.

4. Hands-On Data Science and Machine Learning in Undergraduate Education

   Courses | 07 Oct 2020 | Contributor(s):: Alejandro Strachan, Saaketh Desai, Juan Carlos Verduzco Gastelum, Michael N Sakano, Zachary D McClure, Joseph M. Cychosz, Jared Gray West

   This series of modules introduce key concepts in data science in the context of application in materials science and engineering.

5. Module 7: Active Learning for Design of Experiments

   Online Presentations | 30 Sep 2020 | Contributor(s):: Alejandro Strachan, Juan Carlos Verduzco Gastelum

   This module introduces active learning in the context of materials discovery with hands-on online simulations. Active learning is a subset of machine learning where the information available at a given time is used to decide what areas of space to explore next. In this module, we will explore...

6. Hands-on Sequential Learning and Design of Experiments

   Online Presentations | 29 Apr 2020 | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan

   This tutorial introduces the concept of sequential learning and information acquisition functions and how these algorithms can help reduce the number of experiments required to find an optimal candidate. A hands-on approach is presented to optimize the ionic conductivity of ceramic...

7. Hands-on Data Science and Machine Learning Training Series

   Courses | 21 Apr 2020 | Contributor(s):: Alejandro Strachan, Saaketh Desai, Arun Kumar Mannodi Kanakkithodi

   his series of workshops introduces participants to important concepts and techniques in data science and machine learning in the context engineering and physical sciences applications. All workshops include hands-on activities.

8. Apr 20 2020

   Sequential learning and design of experiments

   Topics covered in this session:Hands-on sequential learningInformation acquisition functions and dynamic plotting of resultsOrganizers: Alejandro Strachan, Saaketh DesaiLeader: Juan Carlos...

   https://nanohub.org/events/details/1845

9. Citrine Tools for Materials Informatics

   Tools | 05 Dec 2019 | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan

   Jupyter notebooks for sequential learning in the context of materials design. Run your own models, explore various methods and adapt the notebooks to your needs.

10. ECE 695E: An Introduction to Data Analysis, Design of Experiment, and Machine Learning

    Courses | 07 Jan 2019 | Contributor(s):: Muhammad A. Alam

    This course will provide the conceptual foundation so that a student can use modern statistical concepts and tools to analyze data generated by experiments or numerical simulation.