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230t2-group3

adia

adv_fin_ml

Solutions for selected exercises from Advances in Financial Machine Learning by Marcos Lopez De Prado

advanced_python_session

UC Berkeley MFE advanced python session

afml

All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.

best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

caffe

Caffe: a fast open framework for deep learning.

datacamp_tutorials

environmental-hackathon

https://environmentalhack.com/

finbert

BERT for Finance : UC Berkeley MIDS w266 Final Project

grokking-deep-learning-with-julia

kaggle-api

Official Kaggle API

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.

quantitativeeasingeffects_equities

Analyze the effect of Quantitative Easing and liquidity injection on the stock market. Observe the different types of stocks that outperform the broader markets during QE and QT

quantresearch

Quantitative analysis, strategies and backtests

quantstats

Portfolio analytics for quants, written in Python

rnn-time-series-anomaly-detection

RNN based Time-series Anomaly detector model implemented in Pytorch.

slow-momentum-fast-reversion

This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (https://arxiv.org/pdf/2105.13727.pdf).

the-elements-of-statistical-learning

My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman

the-elements-of-statistical-learning-python-notebooks

A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book

trading-momentum-transformer

This code accompanies the the paper Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture (https://arxiv.org/pdf/2112.08534.pdf).