Beast code in Giters

Jianxin Yang's starred repositories

Python

All Algorithms implemented in Python

hello-algo

《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新，English version ongoing

Language:JavaNOASSERTION90026 514 208

C-Plus-Plus

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

Language:C++MIT29712 515 286

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

Language:C++Apache-2.025884 912 5227

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

Language:Jupyter NotebookNOASSERTION21766 1482 122

tensorflow2_tutorials_chinese

tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials

Language:Jupyter Notebook7781 312 21

kopia

Cross-platform backup tool for Windows, macOS & Linux with fast, incremental backups, client-side end-to-end encryption, compression and data deduplication. CLI and GUI included.

Language:GoApache-2.06833 53 1319

deap

Distributed Evolutionary Algorithms in Python

Language:PythonLGPL-3.05693 192 512

mesa

Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors.

Language:PythonNOASSERTION2318 92 742

fantastic-matplotlib

Matplotlib中文教程，在线阅读地址：https://datawhalechina.github.io/fantastic-matplotlib/

Language:PythonNOASSERTION449 5 3

30DayMapChallenge2019

My contributions to the #30DayMapChallenge 2019, a daily challenge focusing on spatial visualizations happening throughout November.

Language:HTML187 6 1

EMAworkbench

workbench for performing exploratory modeling and analysis

Language:Jupyter NotebookBSD-3-Clause124 10 156

pareto.py

Nondominated sorting for multi-objective problems

Language:PythonLGPL-3.0112 12 33

SOFTX_2020_1

An intuitive library to extract features from time series. To cite this software publication: https://www.sciencedirect.com/science/article/pii/S2352711020300017

Language:Jupyter NotebookBSD-3-Clause91 30

PRIM

Patient Rule Induction Method (PRIM) for Python

Language:PythonGPL-3.049 3 3

The Mixed-Cell Cellullar Automata (MCCA) provides a new approach to enable more dynamic mixed landuse modeling to move away from the analysis of static patterns. One of the biggest advantages of mixed-cell CA models is the capability of simulating the quantitative and continuous changes of multiple landuse components inside cells.

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