Pinned Repositories
Actor-Critic-Methods-Paper-To-Code
Adv_Fin_ML_Exercises
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
advanced-python-programming
Course by David Beazley
backtrader
Python Backtesting library for trading strategies
CFTC-COT
Parses historical and current CFTC Commitments of Traders reports into easy-to-use pandas dataframes
code-with-engineering-playbook
This is the playbook for "code-with" customer or partner engagements
coroutines
A Curious Course on Coroutines and Concurrency - David Beazley
dnnrec_eswa
finalexp34
efpm04013's Repositories
efpm04013/advanced-python-programming
Course by David Beazley
efpm04013/backtrader
Python Backtesting library for trading strategies
efpm04013/code-with-engineering-playbook
This is the playbook for "code-with" customer or partner engagements
efpm04013/dabeaz-compilers
Code for David Beazley's compilers course, June 2019
efpm04013/D2L-Torch
Learning PyTorch through the D2L book. A series of notebooks for the same
efpm04013/DeepReinforcementLearningInAction
Code from the Deep Reinforcement Learning in Action book from Manning, Inc
efpm04013/Ehlers-Homodyne-Discriminator-Python
First test case
efpm04013/featurebyte
Python Library for FeatureOps
efpm04013/financial-machine-learning
A curated list of practical financial machine learning tools and applications.
efpm04013/hangukquant.github.io
Documentation for hangukquant/quantpylib
efpm04013/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
efpm04013/Microsoft-Azure-Algotrading101
Live Algo Trading on the Cloud - Microsoft Azure
efpm04013/ml-engineering
Machine Learning Engineering Guides and Tools
efpm04013/MLFINLAB-1
public version of MLFINLAB from Hudson-Thames
efpm04013/mlfinlab_sandorabad
efpm04013/practical-python
Practical Python Programming (course by @dabeaz)
efpm04013/pysystemtrade
Systematic Trading in python
efpm04013/python-training
Python training for business analysts and traders
efpm04013/qlib
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.
efpm04013/quant-finance-lectures
Learn quantitative finance with this comprehensive lecture series. Adapted from the Quantopian Lecture Series. Uses free sample data.
efpm04013/quantstats
Portfolio analytics for quants, written in Python
efpm04013/quanttrader
Backtest and live trading in Python
efpm04013/Raft_Python
efpm04013/reports
Automatically generated reports and diagnostics of interest to futures traders
efpm04013/sapy
Python code and data to the manuscript "Hands-on Signal Analysis with Python"
efpm04013/stop-trading
A starter code to review distribution of a strategy returns and assess Monte Carlo distribution of returns
efpm04013/volatility-trading
A complete set of volatility estimators based on Euan Sinclair's Volatility Trading
efpm04013/VolTinker
Applying the ideas in Euan Sinclair's "Volatility Trading"
efpm04013/wabbit_dbeazley
Compiler project for Dave Beazley' Wabbit Language
efpm04013/zingg
Scalable identity resolution, entity resolution, data mastering and deduplication using ML