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Machine Learning in Physics
04 Nov 2021 | Contributor(s):: Nicolas Onofrio
Lectures and tutorials to learn how to write machine learning programs with Python
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Module 5: Neural Networks for Regression and Classification
Online Presentations | 01 Oct 2020 | Contributor(s):: Saaketh Desai, Alejandro Strachan
This module introduces neural networks for material science and engineering with hands-on online simulations. Neural networks are a subset of machine learning models used to learn mappings between inputs and outputs for a given dataset. Neural networks offer great flexibility and have shown...
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Module 4: Linear Regression Models
Online Presentations | 01 Oct 2020 | Contributor(s):: Michael N Sakano, Saaketh Desai, Alejandro Strachan
This module introduces linear regression in the context of materials science and engineering. We will apply liner regression to predict materials properties and to explore correlations between materials properties via hands-on online simulations. Linear regression is a supervised machine...
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Linear Regression Young's modulus
Tools | 24 Sep 2020 | Contributor(s):: Michael N Sakano, Saaketh Desai, Alejandro Strachan
Use linear regression to extract Young's modulus and yield stress from stress-strain data
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Machine Learning in Materials - Center for Advanced Energy Studies and Idaho National Laboratory
Presentation Materials | 24 Sep 2020 | Contributor(s):: Alejandro Strachan
his hands-on tutorial will introduce participants to modern tools to manage, organize, and visualize data as well as machine learning techniques to extract information from it. ...
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ECE 595ML Lecture 1.2: Linear Regression - Geometry
Online Presentations | 28 May 2020 | Contributor(s):: Stanley H. Chan
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Hands-on Supervised Learning: Part 1 - Linear Regression and Neural Networks
Online Presentations | 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:...
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ECE 595ML Lecture 13.2: Connecting Bayesian with Linear Regression
Online Presentations | 24 Mar 2020 | Contributor(s):: Stanley H. Chan
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ECE 595ML Lecture 13.1: Connecting Bayesian with Linear Regression - Linear Regression Review
Online Presentations | 17 Feb 2020 | Contributor(s):: Stanley H. Chan
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Data Science and Machine Learning for Materials Science
Online Presentations | 22 Jan 2020 | Contributor(s):: Saaketh Desai
This talk covers the fundamentals of machine learning and data science, focusing on material science applications. The talk is for a general audience, attempting to introduce basic concepts such as linear regression, supervised learning with neural networks including forward and back...
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ECE 595ML Lecture 1.1: Linear Regression
Online Presentations | 21 Jan 2020 | Contributor(s):: Stanley H. Chan
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ECE 595ML Lecture 2.1: Regularized Linear Regression
Online Presentations | 21 Jan 2020 | Contributor(s):: Stanley H. Chan
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Machine Learning for Materials Science: Part 1
Tools | 09 Feb 2019 | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan, Saaketh Desai
Machine learning and data science tools applied to materials science