Arthur-Wellesley

Arthur-Wellesley's Stars

• Lancephil/Dung-Beetle-Optimizer

  Matlab and Python code of Dung Beetle Optimizer

  Language:MATLAB305

• ultralytics/yolov5

  YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

  Language:Python50.9k16.4k

• ultralytics/ultralytics

  Ultralytics YOLO11 🚀

  Language:Python32.5k6.3k

• PeterRochford/SkillMetrics

  A Python library for calculating and displaying the skill of model predictions against observations.

  Language:Python20192

• 7ossam81/EvoloPy

  EvoloPy toolbox provides classical and recent nature-inspired metaheuristic for the global optimization.

  Language:Jupyter Notebook450225

• bayesian-optimization/BayesianOptimization

  A Python implementation of global optimization with gaussian processes.

  Language:Python7.9k1.5k

• federhub/pyGRNN

  Python implementation of General Regression Neural Network (Nadaraya-Watson Estimator). A Feature Selection module based on GRNN is also provided

  Language:Jupyter Notebook7424

• fengdu78/lihang-code

  《统计学习方法》的代码实现

  Language:Jupyter Notebook19k6.3k

• mattsherar/Temporal_Fusion_Transform

  Pytorch Implementation of Google's TFT

  Language:Jupyter Notebook24160

• LeBron-Jian/MachineLearningNote

  Language:Jupyter Notebook492211

• fuzhipeng/breast_cancer_data

  乳腺癌检测分类数据

  11

• dmlc/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++26.3k8.7k

• ranjiewwen/machinelearninginaction

  Source Code for the book: Machine Learning in Action published by Manning

  Language:HTML2

• mehul90/NSE_TRADER

  A basic implementation to download historic prices, apply a strategy, and see the strategy performance vis-a-vis the actual stock prices.

  Language:Python4343

• Sevistuo/h2o-3

  Open Source Fast Scalable Machine Learning Platform For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), ...)

  Language:Java1

• tongzm/ml-python

  Language:Jupyter Notebook376344

• myazi/myLearn

  machine learning algorithm

  Language:C++16262

• a-bean-sprout/XGBoost_StockPricePredict

  Attempt to use XGBoost in stock price prediction

  Language:Python8323

• HannH/SimpleRNN

  simple implement of LSTM and GRU

  Language:Python56

• dennybritz/rnn-tutorial-gru-lstm

  Language Model GRU with Python and Theano

  Language:Python496219

• robinroche/jica

  A Java implementation of the Imperialist Competitive Algorithm (ICA), an optimization algorithm

  Language:Java82

• karpathy/Random-Forest-Matlab

  A Random Forest implementation for MATLAB. Supports arbitrary weak learners that you can define.

  Language:Matlab182121

• shiluqiang/RBF_NN_Python

  Python code of RBF neural network classification model

  Language:Python4327

• donnemartin/data-science-ipython-notebooks

  Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

  Language:Python27.5k7.9k

• tushushu/imylu

  Pure Python implementation of machine learning algorithms

  Language:Python442255

• Vambooo/lihang-dl

  Language:Jupyter Notebook146

• sfeng-m/tree-model

  Tree model with detailed explanation

  Language:Python10295

• apachecn/ailearning

  AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

  Language:Python39.5k11.4k

• nsfinkelstein/hierarchical-rnn

  Tensorflow implementation of a Hierarchical and Multiscale RNN, described in https://arxiv.org/abs/1609.01704

  Language:Jupyter Notebook13547

• pingfangx/TranslatorX

  JetBrains 系列软件汉化包 关键字: Android Studio 3.5 汉化包 CLion 2019.3 汉化包 DataGrip 2019.3 汉化包 GoLand 2019.3 汉化包 IntelliJ IDEA 2019.3 汉化包 PhpStorm 2019.3 汉化包 PyCharm 2019.3 汉化包 Rider 2019.3 汉化包 RubyMine 2019.3 汉化包 WebStorm 2019.3 汉化包

  Language:HTML4.6k616