zhaohan-dong

zhaohan-dong's Stars

• nlohmann/json

  JSON for Modern C++

  Language:C++44.4k7582.3k6.9k

• karpathy/llama2.c

  Inference Llama 2 in one file of pure C

  Language:C18k1922242.2k

• fail2ban/fail2ban

  Daemon to ban hosts that cause multiple authentication errors

  Language:Python13.2k2532.3k1.3k

• GoogleCloudPlatform/training-data-analyst

  Labs and demos for courses for GCP Training (http://cloud.google.com/training).

  Language:Jupyter Notebook8k2822245.9k

• py-why/dowhy

  DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

  Language:Python7.3k140484944

• ml-explore/mlx-examples

  Examples in the MLX framework

  Language:Python6.9k77580977

• kernc/backtesting.py

  :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.

  Language:Python6k1235171.1k

• lballabio/QuantLib

  The QuantLib C++ library

  Language:C++5.7k2626281.8k

• py-why/EconML

  ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

  Language:Jupyter Notebook4k77585735

• pmorissette/bt

  bt - flexible backtesting for Python

  Language:Python2.4k94346436

• databricks/LearningSparkV2

  This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]

  Language:Scala1.2k4022755

• sunknudsen/privacy-guides

  Privacy guides reference material (archived)

  Language:Shell836355998

• je-suis-tm/web-scraping

  Detailed web scraping tutorials for dummies with financial data crawlers on Reddit WallStreetBets, CME (both options and futures), US Treasury, CFTC, LME, MacroTrends, SHFE and alternative data crawlers on Tomtom, BBC, Wall Street Journal, Al Jazeera, Reuters, Financial Times, Bloomberg, CNN, Fortune, The Economist

  Language:Python7632910175

• jaege/Cpp-Primer-5th-Exercises

  Solutions to Exercises in C++ Primer 5th Edition

  Language:C++7413333248

• microsoft/causica

  Language:Python464124355

• iains/gcc-darwin-arm64

  GCC master branch for Darwin with experimental support for Arm64. Currently GCC-15.0.1 [February 2025]

  Language:C++2761912133

• microsoft/showwhy

  Language:TypeScript209123627

• safellama/plexiglass

  A toolkit for detecting and protecting against vulnerabilities in Large Language Models (LLMs).

  Language:Python1297714

• ml-explore/mlx-c

  C API for MLX

  Language:C++95141124

• Fahien/excpp

  :pencil: Solutions to exercises in the Bjarne Stroustrup's textbook The C++ Programming Language, 4th Edition

  Language:C++23203