Roll-to-Roll Manufacturing Data Ingestion
12 Sep 2023 | Contributor(s):: Alejandro Strachan, Richard S Hosler, Juan Carlos Verduzco Gastelum
Roll-to-Roll Manufacturing Data Ingestion tool to process data for the r2rdatabase sim2l
A Guided Tour of Interactive Jupyter Notebooks Powered by nanoHUB
20 Feb 2023 | | Contributor(s):: Daniel Mejia
In this presentation, we will take you on a guided tour of interactive Jupyter Notebooks powered by nanoHUB. Jupyter is a powerful tool for data science and scientific computing that provides an intuitive interface for a variety of programming languages; Jupyter in nanoHUB provides even more...
No-code ML models
18 Oct 2022 | | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan
No-code ML models
Data Cleaning with MATLAB
12 Oct 2022 | | Contributor(s):: Kelsey Joy Rodgers
This workshop will go over MATLAB built-in functions (readcell and writecell) to import data from Excel and export data to Excel.
The Materials Simulation Toolkit for Machine Learning (MAST-ML): Automating Development and Evaluation of Machine Learning Models for Materials Property Prediction
06 Oct 2022 | | Contributor(s):: Ryan Jacobs
Hands-on activities, we will use MAST-ML to (1) import materials datasets from online databases and clean and examine our input data, (2) conduct feature engineering analysis, including generation, preprocessing, and selection of features, (3) construct, evaluate and compare the performance of...
Aug 10 2022
Machine Learning Predicts Additive Manufacturing Part Quality: Tutorial on Support Vector Regression
Querying Materials Data Repositories
05 Aug 2022 |
Posted by Tanya Faltens
ANN Model Generator
11 Jul 2022 | | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan
Simtool workflow to create ANN models for user datasets
Apr 13 2022
Message-Passing Neural Networks for Molecular Property Prediction Using Chemprop
Learning and Teaching Data Science using nanoHUB’s Cloud Resources
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.
Machine Learning with MATLAB
11 Mar 2022 | | Contributor(s):: Gaby Arellano Bello
In this session, we explore the fundamentals of machine learning using MATLAB. We introduce machine learning techniques available in MATLAB to quickly explore your data, evaluate machine learning algorithms, compare the results and apply the best technique to your problem.
Data Analysis with MATLAB
04 Mar 2022 | | Contributor(s):: Gen Sasaki
Learn how MATLAB can be used to visualize and analyze data, perform numerical computations, and develop algorithms. Through live demonstrations and examples, you will see how MATLAB can help you become more effective in your coursework as well as in research.
09 Sep 2021 | | Contributor(s):: Gen Sasaki, Lisa Kempler
MATLAB is a programming and numeric computing platform to analyze data, develop algorithms, and create models.
Introduction to dplyr, ggplot2 and Other tidyverse Friends: Modern Tools for Data Exploration and Visualization
08 Jul 2021 | | Contributor(s):: Rei Sanchez-Arias
In recent years, interest in the development of predictive models and the use of machine learning libraries has grown rapidly. As part of the efficient implementation of different models, a fundamental component of this process deals with data preparation and cleaning, followed by exploration,...
Utilizing Modern Data Exploration and Visualization Tools for STEM Applications and Datasets
If you're an instructor in a STEM field who wants to add a data science component to an existing course, this series will give you the tools. You'll leave these sessions with practical knowledge that will empower your students.Topics include:Data preparation and cleaningData...
25 Jun 2021 | | Contributor(s):: Ryan Jacobs
This tutorial contains an introduction to the use of the Materials Simulation Toolkit for Machine Learning (MAST-ML), a python package designed to broaden and accelerate the use of machine learning and data science methods for materials property prediction.
tidyverse Data Science Tools for STEM Applications and Datasets
25 Jun 2021 | | Contributor(s):: Rei Sanchez-Arias
An introduction to dplyr, ggplot2, and other tidyverse data science tools in STEM applications
Victor Wealth Adankai
Sheimy Paz Serpa
A Hands-on Introduction to Physics-Informed Neural Networks
16 Jun 2021 | | Contributor(s):: Ilias Bilionis, Atharva Hans
Can you make a neural network satisfy a physical law? There are two main types of these laws: symmetries and ordinary/partial differential equations. I will focus on differential equations in this short presentation. The simplest way to bake information about a differential equation with neural...