tengjuilin
Dedicated and detail-oriented Ph.D. student at UC Berkeley interested in the intersection of chemical engineering, bionanotechnology, and data science.
University of California, BerkeleyBerkeley, CA
tengjuilin's Stars
pytorch/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
CSSEGISandData/COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
ageron/handson-ml2
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.
matterport/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
zergtant/pytorch-handbook
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
lyhue1991/eat_tensorflow2_in_30_days
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
milesial/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
mrdbourke/machine-learning-roadmap
A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
zhixuhao/unet
unet for image segmentation
TrickyGo/Dive-into-DL-TensorFlow2.0
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现,项目已得到李沐老师的认可
jckantor/CBE20255
Introduction to Chemical Engineering Analysis
SabrinaSun1225/ChromaPalette
tengjuilin/markdown-resume
A simple, elegant, and fast workflow to write resumes and CVs in Markdown.
tengjuilin/equation-sheets
Equation sheets of STEM courses at the University of Washington (UW). Topics include chemistry, physics, calculus, applied mathematics, and chemical engineering.
tengjuilin/cheme-sci-computing
UW CHEME 375 and applications in CHEME 310, 326. Chemical engineering scientific computing and numerical methods. Topics include curve fitting, balancing chemical equations, solving VLE problems, plotting VLE x/y and Txy diagrams, determining Antoine's coefficients, chemical kinetics, and time-dependent and -independent heat transfer.
tengjuilin/intro-sci-computing
UW AMATH 301. Scientific computing and numerical methods for physical, biological, and engineering problems. Topics include root-finding, optimization, curve fitting, solving linear systems, singular value decomposition (SVD, PCA), numerical differentiation and integration, solving first-order and higher order ODEs, stability and stiffness of ODEs, phase portraits, chaotic systems, and Fourier transform.
tengjuilin/orbit-simulation
An orbit simulation of a rocket/satellite launched from the Earth that performs Homann transfer and orbits around the Moon.
NicholasOuassil/swnt-protein-corona-ML
Ensemble classifiers and data scraping tools for the prediction of protein surface adsorption to single-walled carbon nanotubes
tengjuilin/course-notes
Course notes of STEM courses at the University of Washington (UW). Topics include chemical engineering, chemistry, and applied mathematics.
GalvinGao/iHomework
iHomework - Student Service Platform