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To predict radon levels in U.S homes by applying deep learning model (Sequential Model)
Deep-Learning-to-find-Superconductors
A collection of drug discovery tools
Supplementary material accompanying Frey, N. C.; Akinwande, D.; Jariwala, D.; Shenoy, V. B. Machine Learning-Enabled Design of Point Defects in 2D Materials for Quantum and Neuromorphic Information Processing, ACS Nano (2020).
Code associated with "A Deep-Learning View of Chemical Space Designed to Facilitate Drug Discovery"
Utilities for transition metal dichalcogenide DFT and Wannier analysis, including transverse electric field and interlayer displacement
DMFT calculations and Machine Learning prediction of Mott transition.
An open source python library for scalable Bayesian optimisation.
Drug Discovery using Machine Learning (For Breast Cancer and Alzheimer Disease)
Drug discovery project by making use of the Tox-21 dataset.
A computational drug discovery project, in which bioinformatic and machine learning tools are used to identify possible molecular targets and drug chemical features to treat prostate cancer
DScribe is a python package for creating machine learning descriptors for atomistic systems.
A module for ASE for elastic constants calculation.
ElATools: A tool for analyzing anisotropic elastic properties of the 2D and 3D materials
Python modules for electron–phonon models
Article template for an Elemental Microscopy article
Electron-Phonon Coupling (EPC) calculation in Quantum Espresso program with q-mesh and irreducible representation splitting
Modified EPW code for first principles calculation of electron transport and thermoelectric property of materials, including electron-phonon scattering, defect scattering, and phonon drag.
ERC Proposal template (StG, CoG, AdG)
ERLabPy provides tools and utilities to handle, manipulate, and visualize data from angle-resolved photoemission spectroscopy (ARPES) experiments.
Notes and tutorials on density functional theory calculations using Quantum Espresso.
Chemist AI Agent for Developing Materials Datasets with Natural Language Prompts
Example usage of Exabyte.io platform through its RESTful API: programmatically create materials and modeling workflows, execute simulations on the cloud, analyze data and build machine learning models
Explainer for black box models that predict molecule properties
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
The world's simplest facial recognition api for Python and the command line
:mag: A python library to discover and mitigate biases in machine learning models and datasets :mag:
Blazing fast symbolic regresison
Finite DIfference microMAGnetic code, based on Python, Cython and C
recipes for making figures (plotting)
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.