jagar2 Goto Github PK
Name: Joshua C Agar
Type: User
Company: Drexel University
Bio: Assistant Professor Department of Mechanical Engineering and Mechanics Drexel University
Blog: M3-learning.com
Name: Joshua C Agar
Type: User
Company: Drexel University
Bio: Assistant Professor Department of Mechanical Engineering and Mechanics Drexel University
Blog: M3-learning.com
A community dedicated to supporting tools for technical and scientific communication and interactive computing
Modules used by contributors to enable their data submissions via MP's contribution framework
A napari plug-in that uses UMAP to identify image similarity for labeling
Official webpage of the Programming Group on https://programming-group.com
The fundamental package for scientific computing with Python.
A collection of packages and tools for electron microscopy data analysis supported by the National Center for Electron Microscopy facility of the Molecular Foundry
Optimization of strain gradient in Phase Field
A WebGL viewer for UMAP or TSNE-clustered images
A Visualization Tool for Image-based Machine Learning Projects - Great for object-detection and image classification projects
Utilities for scientific analysis of nanoscale imaging data
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Modular data acquisition framework
The ability to manipulate domains and domain walls underpins function in a range of next-generation applications of ferroelectrics. While there have been demonstrations of controlled nanoscale manipulation of domain structures to drive emergent properties, such approaches lack an internal feedback loop required for automation. Here, using a deep sequence-to-sequence autoencoder we automate the extraction of features of nanoscale ferroelectric switching from multichannel hyperspectral band-excitation piezoresponse force microscopy of tensile-strained PbZr0.2Ti0.8O3 with a hierarchical domain structure. Using this approach, we identify characteristic behavior in the piezoresponse and cantilever resonance hysteresis loops, which allows for the classification and quantification of nanoscale-switching mechanisms. Specifically, we are able to identify elastic hardening events which are associated with the nucleation and growth of charged domain walls. This work demonstrates the efficacy of unsupervised neural networks in learning features of the physical response of a material from nanoscale multichannel hyperspectral imagery and provides new capabilities in leveraging multimodal in operando spectroscopies and automated control for the manipulation of nanoscale structures in materials.
Scikit-learn tutorial at SciPy2016
Tutorial material on the scientific Python ecosystem
SparsePTO
Introduces basic methods and code development tools for scientific computing in the Python language, including coding, analysis, data fitting, visualization, importing/exporting information, multidimensional analysis, and visualization using Python and its packages MatPlotlib, NumPy, SciPy. Basic statistical methods, distributions, data fitting and error analysis will be discussed with a focus on relevancy for material scientists and engineers. In addition to numerical approaches, symbolic problem solving will be discussed. Integration of external data sets, databases queries, and collective tools into computational methods are introduced.
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2021/Spring 2022
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.