HeleneZhg

HeleneZhg's Stars

• eugeneyan/applied-ml

  📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

  27.3k3.7k

• ossu/computer-science

  🎓 Path to a free self-taught education in Computer Science!

  172k21.7k

• SJD1882/Paris-Dauphine-Master-203-Projects

  Personal Repository for School Projects from Paris-Dauphine's Master 203 Financial Markets (Algorithmic Trading, C++, Machine Learning).

  Language:C++4

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook22.8k3.3k

• dennybritz/reinforcement-learning

  Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

  Language:Jupyter Notebook20.5k6k

• maelfabien/Machine_Learning_Tutorials

  Code, exercises and tutorials of my personal blog ! 📝

  Language:Jupyter Notebook777258

• raghakot/keras-vis

  Neural network visualization toolkit for keras

  Language:Python3k661

• khanhnamle1994/cracking-the-data-science-interview

  A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

  Language:Jupyter Notebook3.7k1k

• yunjey/pytorch-tutorial

  PyTorch Tutorial for Deep Learning Researchers

  Language:Python30.1k8.1k

• lopusz/awesome-interpretable-machine-learning

  Language:Python904141

• tensorflow/lucid

  A collection of infrastructure and tools for research in neural network interpretability.

  Language:Jupyter Notebook4.7k653

• MaxHalford/prince

  :crown: Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA

  Language:Python1.3k184

• Rachnog/Deep-Portfolio-Management

  Source code for the blog post on the evolution of the asset allocation methods

  Language:Jupyter Notebook212105

• robertmartin8/PyPortfolioOpt

  Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

  Language:Jupyter Notebook4.5k957

• wilsonfreitas/awesome-quant

  A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

  Language:Python18k2.6k

• tensorflow/neural-structured-learning

  Training neural models with structured signals.

  Language:Python982189

• derekgreene/topic-model-tutorial

  Tutorial on topic models in Python with scikit-learn

  Language:Jupyter Notebook15650

• tonio73/dnnviewer

  Deep Neural Network viewer

  Language:Jupyter Notebook182

• yzhao062/SUOD

  (MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)

  Language:Python37949

• albertcthomas/anomaly_tuning

  Learning hyperparameters for unsupervised anomaly detection

  Language:Jupyter Notebook3713

• titu1994/Wide-Residual-Networks

  Wide Residual Networks in Keras

  Language:Python11244

• GAA-UAM/scikit-fda

  Functional Data Analysis Python package

  Language:Python30158

• sugi-chan/fgo-multi-task-keras

  multiclass classification example using keras and fgo

  Language:Jupyter Notebook1812

• eamid/trimap

  TriMap: Large-scale Dimensionality Reduction Using Triplets

  Language:Python30420

• bethgelab/foolbox

  A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

  Language:Python2.8k426

• wangyangparis/DataChallenge2020

  Language:Jupyter Notebook5

• quantopian/pyfolio

  Portfolio and risk analytics in Python

  Language:Jupyter Notebook5.7k1.8k

• maciejkula/spotlight

  Deep recommender models using PyTorch.

  Language:Python3k423

• aksnzhy/xlearn

  High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

  Language:C++3.1k518

• NicolasHug/Surprise

  A Python scikit for building and analyzing recommender systems

  Language:Python6.4k1k