rvraghvender

rvraghvender's Stars

• petermattia/battery-parameter-spaces

  Battery fast-charging parameter spaces

  Language:Jupyter Notebook2413

• chueh-ermon/BMS-autoanalysis

  Language:MATLAB4521

• rdbraatz/data-driven-prediction-of-battery-cycle-life-before-capacity-degradation

  Code for Nature energy manuscript

  Language:Jupyter Notebook498197

• TRI-AMDD/beep

  Battery evaluation and early prediction

  Language:Python13262

• Battery-Intelligence-Lab/SLIDE

  SLIDE is C++ code that simulates degradation of lithium ion cells. It extends the single particle model with various degradation models from literature. Users can select which degradation models they want to use for a given simulation.

  Language:C++11834

• naveenedoth/pybamm

  Language:Jupyter Notebook2

• GokuMohandas/Made-With-ML

  Learn how to design, develop, deploy and iterate on production-grade ML applications.

  Language:Jupyter Notebook37.9k6k

• lmmentel/awesome-python-chemistry

  A curated list of Python packages related to chemistry

  1.2k216

• jkitchin/dft-book

  A book on modeling materials using VASP, ase and vasp

  Language:Python354140

• sedaoturak/data-resources-for-materials-science

  A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.

  28348

• goerz/fortran_examples

  Fortran example programs for Intro to Computational Physics

  Language:Fortran112

• entbappy/PyTorch

  Language:Jupyter Notebook41

• IvanIsCoding/ResuLLMe

  Enhance your résumé with Large Language Models

  Language:Python33992

• singhsourabh/Resume-NER

  Applying BERT for named entity recognition on resumes.

  Language:Python6125

• jungsoh/facenet-face-verification-and-face-recognition

  Application of pre-trained FaceNet to face verification and face recognition problems face-recognition facenet keras-models triplet-loss face-verification inception-network face-encoding

  Language:Jupyter Notebook22

• ageron/handson-ml3

  A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

  Language:Jupyter Notebook8.1k3.3k

• krishnaik06/Complete-Langchain-Tutorials

  Language:Jupyter Notebook367308

• zoowe/dlePy

  dlePy

  Language:Python85

• zaba1157/materials_workflows

  Language:Python51

• jic198/aimsflow

  Language:Python1

• ferbachega/pepdice3

  Language:Python1

• kbsezginel/angstrom

  Ångström, a Python package for molecular architecture and visualization

  Language:Python195