pcassell's Stars
quantopian/alphalens
Performance analysis of predictive (alpha) stock factors
microsoft/AI-For-Beginners
12 Weeks, 24 Lessons, AI for All!
xsudoxx/OSCP
sherlock-project/sherlock
Hunt down social media accounts by username across social networks
her0marodeur/awesome-free-cybersecurity
A curated list of free cybersecurity learning resources.
ReagentX/imessage-exporter
Export iMessage data + run iMessage Diagnostics
kccqzy/imessage-db-extract
Extract messages from an iMessage database from iOS 8
stephancasas/alfred-mouseless-messenger
Preview and reply to your messages from within Alfred. Keep your hands on that keyboard!
premAI-io/state-of-open-source-ai
:closed_book: Clarity in the current fast-paced mess of Open Source innovation
alex/what-happens-when
An attempt to answer the age old interview question "What happens when you type google.com into your browser and press enter?"
ranlo/osintsummit-2023-resources
A categorized list of resources presented during the 2023 Sans OSINTSummit
chrisconlan/algorithmic-trading-with-python
Source code for Algorithmic Trading with Python (2020) by Chris Conlan
cuemacro/findatapy
Python library to download market data via Bloomberg, Eikon, Quandl, Yahoo etc.
huseinzol05/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
cantaro86/Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
santoshlite/Empyrial
An Open Source Portfolio Backtesting Engine for Everyone | 面向所有人的开源投资组合回测引擎
man-group/arctic
High performance datastore for time series and tick data
rubenafo/yfMongo
MongoDb tool to store stock Yahoo Finance market data in a consistent way
pmorissette/bt
bt - flexible backtesting for Python
kernc/backtesting.py
:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
hjeffreywang/Stock_feature_engineering
Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. Generated features from indicators, statistics, and recent factors. Used multi-disciplined analysis to find feature importance. Attached labels of trends and stop/hold positions for machine learning. Used machine learning to significant features.
mhallsmoore/qstrader
QuantStart.com - QSTrader backtesting simulation engine.
wesm/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
fchollet/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
eriklindernoren/ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Experience-Monks/math-as-code
a cheat-sheet for mathematical notation in code form
hudson-and-thames/mlfinlab
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
ageron/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
firmai/machine-learning-asset-management
Machine Learning in Asset Management (by @firmai)
r0f1/datascience
Curated list of Python resources for data science.