nuel-ol's Stars
getify/You-Dont-Know-JS
A book series on JavaScript. @YDKJS on twitter.
pwlnk/focus-stacking
Simple implementation of focus stacking technique.
pwlnk/cuda-neural-network
Simple neural network implementation using CUDA technology. It is an educational implementation.
jump-dev/JuMPTutorials.jl
Tutorials on using JuMP for mathematical optimization in Julia
Pyomo/pyomo
An object-oriented algebraic modeling language in Python for structured optimization problems.
milliams/data_analysis_python
Course notes for the Data Analysis in Python course
damirlj/modern_cpp_tutorials
Tutorials in modern c++
NVIDIA/CUDALibrarySamples
CUDA Library Samples
karpathy/llm.c
LLM training in simple, raw C/CUDA
ChrisRackauckas/AutumnSchool2023
Course material for the autumn school in scienfic machine learning 2023
ChrisRackauckas/ParameterEstimation.jl
ParameterEstimation.jl is a Julia package for estimating parameters and initial conditions of ODE models given measurement data.
SciML/SciMLBook
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
abdelrahmaan/Financial-aid-on-coursera-
Applying for financial aid on coursera
AB-Blue/Seismic-Data-Interactive-Visualization-2D-3D
2D/3D post-stack seismic amplitude/reservoir property in sgy/segy format
Skoltech-CHR/DeepField
Machine learning framework for reservoir simulation
ventZl/cmrx
C Microkernel Realtime eXecutive
akalenuk/the_namingless_programming_language
Naming is hard. How far can we go without?
FHoltorf/LowRankArithmetic.jl
Package for the propagation of representations of low-rank matrices through finite compositions of common operations.
FHoltorf/LowRankIntegrators.jl
Package for approximation of solutions to matrix differential equations or time-dependent matrices via dynamically evolving low rank decomposition.
pyg-team/pytorch_geometric
Graph Neural Network Library for PyTorch
DataTalksClub/machine-learning-zoomcamp
Learn ML engineering for free in 4 months!
CynthiaPeter/Technical-Writing-Resources
A collection of blogpost, resources, and links that has helped me in my journey as a technical writer. I still refer to them and contribute to the list as I find more.
EnesSahin4120/PhysicsEngine
Physics Engine with OpenGL(C++)
ecrc/ExaGeoStatCPP
ar4/agdeblend
Seismic data blending and deblending
calebxyz/safe_cast
safe reinterpreted casts with std::bit_cast
pdeitel/CPlusPlusHowToProgram10e
C++ How to Program, 10/e Code Files
AB-Blue/Blueing-Reflectivity-Integration-BRI-
Seismic Spectral Enhancement Technique
kodejuice/x86-assembly-code
KeithGalli/sklearn
Data & Code associated with my tutorial on the sci-kit learn machine learning library in python