ediab's Stars
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
DopplerHQ/awesome-interview-questions
:octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:
OpenBB-finance/OpenBB
Investment Research for Everyone, Everywhere.
sebastianruder/NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
wilsonfreitas/awesome-quant
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
quantopian/zipline
Zipline, a Pythonic Algorithmic Trading Library
rlabbe/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
mementum/backtrader
Python Backtesting library for trading strategies
statsmodels/statsmodels
Statsmodels: statistical modeling and econometrics in Python
yzhao062/pyod
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
yzhao062/anomaly-detection-resources
Anomaly detection related books, papers, videos, and toolboxes
unit8co/darts
A python library for user-friendly forecasting and anomaly detection on time series.
mwouts/jupytext
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
cantaro86/Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
borisbanushev/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
AllenDowney/ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
man-group/arctic
High performance datastore for time series and tick data
BayesWitnesses/m2cgen
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
afshinea/stanford-cs-221-artificial-intelligence
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence
rmcelreath/statrethinking_winter2019
Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019
PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading
Hands-On Machine Learning for Algorithmic Trading, published by Packt
yhilpisch/py4fi2nd
Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.
dwcoder/QuantitativePrimer
An Interview Primer for Quantitative Finance
chrisvoncsefalvay/learn-julia-the-hard-way
Learn Julia the hard way!
Xtra-Computing/thundergbm
ThunderGBM: Fast GBDTs and Random Forests on GPUs
yhilpisch/dawp
Jupyter Notebooks and code for Derivatives Analytics with Python (Wiley Finance) by Yves Hilpisch.
sahandha/eif
Extended Isolation Forest for Anomaly Detection
mphilli/English-to-IPA
Converts English text to IPA notation
PhantomInsights/summarizer
A Reddit bot that summarizes news articles written in Spanish or English. It uses a custom built algorithm to rank words and sentences.
apas/pomodoro
Minimalist macOS Pomodoro app written in Swift