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blogs

blogs and notes, https://yunchaoyang.github.io/blogs/

bof-imageprocessingtutorial

bof-multigpututorial

bof_pinn

c-cpp-notes

Notes about modern C++, C++11, C++14 and C++17, Boost Libraries, ABI, foreign function interface and reference cards.

cassowary.dart

Cassowary constraint solving algorithm in Dart

cplusplusthings

C++那些事

cpp-cheatsheet

Modern C++ Cheatsheet

cpp-serializers

Benchmark comparing various data serialization libraries (thrift, protobuf etc.) for C++

cpp11_threadpool

A C++11 Thread pool with 3 priorities

cuda-samples

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

cuda_learning_cliff

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

folder-structure-conventions

Folder / directory structure options and naming conventions for software projects

folly

An open-source C++ library developed and used at Facebook.

foundation-models-physics

getting-things-done-with-pytorch

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

github-slideshow

A robot powered training repository :robot:

heart

Heart-Disease-Prediction-using-Machine-Learning Thus preventing Heart diseases has become more than necessary. Good data-driven systems for predicting heart diseases can improve the entire research and prevention process, making sure that more people can live healthy lives. This is where Machine Learning comes into play. Machine Learning helps in predicting the Heart diseases, and the predictions made are quite accurate. The project involved analysis of the heart disease patient dataset with proper data processing. Then, different models were trained and and predictions are made with different algorithms KNN, Decision Tree, Random Forest,SVM,Logistic Regression etc This is the jupyter notebook code and dataset I've used for my Kaggle kernel 'Binary Classification with Sklearn and Keras' I've used a variety of Machine Learning algorithms, implemented in Python, to predict the presence of heart disease in a patient. This is a classification problem, with input features as a variety of parameters, and the target variable as a binary variable, predicting whether heart disease is present or not. Machine Learning algorithms used: Logistic Regression (Scikit-learn) Naive Bayes (Scikit-learn) Support Vector Machine (Linear) (Scikit-learn) K-Nearest Neighbours (Scikit-learn) Decision Tree (Scikit-learn) Random Forest (Scikit-learn) XGBoost (Scikit-learn) Artificial Neural Network with 1 Hidden layer (Keras) Accuracy achieved: 95% (Random Forest) Dataset used: https://www.kaggle.com/ronitf/heart-disease-uci

ib-matlab

2D & 3D Matlab codes for the Immersed Boundary Method

ib2d

An easy to use immersed boundary method in 2D, with full implementations in MATLAB and Python that contains over 60 built-in examples, including multiple options for fiber-structure models and advection-diffusion, Boussinesq approximations, and/or artificial forcing.

imageprocessing2023

labelfree-dnn-surrogate

Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning

learning-python-physics-informed-machine-learning-pinns-deeponets

Physics Informed Machine Learning Tutorials (Pytorch and Jax)

leetcode

Provide all my solutions and explanations in Chinese for all the Leetcode coding problems.

leetcode-1

leetcode的练习记录

machine-learning-collection

A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)

machine_learning_fluid_dynamics

A curated list of awesome Machine Learning projects in Fluid Dynamics

mastering-multithreading-with-cplusplus

Mastering Multithreading with C++, published by Packt

matib

A simple immersed boundary method solver in matlab.