#计算机科学#MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
#Awesome#Quant/Algorithm trading resources with an emphasis on Machine Learning
A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.
algorithmic trading using machine learning
#Awesome#A collection of awesome papers, articles and various resources on credit and credit risk modeling
#计算机科学#🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This ...
#时序数据库#Python library for building financial machine learning models.
It is a Jupyter notebook that compares different trading strategies using technical analysis, machine learning, and deep learning methods.
A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.
#计算机科学#Pricing Financial Options contracts using LightGBM, Deep Learning, and Support Vector Machines.
Implementations of Genetic Methods for Financial Machine Learning Applications
#计算机科学#Financial Machine Learning Repository
#计算机科学#Pytorch implementation of TABL from Temporal Attention Augmented Bilinear Network for Financial Time Series Data Analysis
A tool to detect whether numerals present in Financial Texts are in-claim or out-of-claim
#计算机科学#2024학년도 1학기 MLfinLab Project Team repository
#区块链#A set of financial analytics projects with python.
#计算机科学#Comprehensive analysis of various ML models to detect fraud in financial transactions.
#计算机科学#Two ensemble models made from ensembles of LightGBM and CNN for a multiclass classification problem.
#计算机科学#실전 금융 머신러닝 완벽 분석 / Advances in Financial Machine Learning