Fourier-Bayesian estimation of stochastic volatility models
Code used to run the numerical examples of "Bayesian Approach for Parameter estimation of Continuous-Time Stochastic Volatility Models using FFourier Transform Methods" by Merkle, Saporito and Targino (Statistics & Probability Letters, Vol. 156, 2020). Available here https://www.sciencedirect.com/science/article/pii/S0167715219302469 and here https://arxiv.org/abs/1812.10556
stacked_generalization Implemented machine learning *stacking technic[1]* as handy library in Python. Feature weighted linear stacking is also availab
MBTR is a python package for multivariate boosted tree regressors trained in parameter space.
LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms Based on the work by Smith et al. (2021) Query
High performance Python GLMs with all the features!
RuleFit Implementation of a rule based prediction algorithm based on the rulefit algorithm from Friedman and Popescu (PDF) The algorithm can be used f
Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics
By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
The Ultimate FREE Machine Learning Study Plan
Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco
Disclaimer: This package is WIP. Do not take any APIs for granted. tspreprocess Time series can contain noise, may be sampled under a non fitting rate
A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art
kaggle_titanic_deploy Project to deploy a machine learning model based on Titanic dataset from Kaggle In this project we used the Titanic dataset from
Call of Duty World League: Search & Destroy Outcome Predictions Growing up as an avid Call of Duty player, I was always curious about what factors led
MachineLearning A repository to work on Machine Learning course. Select an algorithm to classify writer's gender, of Hebrew texts. Tested algorithms:
tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis
Decision_Tree_Regression I implemented the decision tree regression algorithm on Python. Unlike regular linear regression, this algorithm is used when
R-Solver A Python tools for deriving R-Type adaptors for Wave Digital Filters. This code is not quite production-ready. If you are interested in contr
machine_learning_examples A collection of machine learning examples and tutorials.
114 Jul 19, 2022
61 Dec 19, 2022
5 Aug 06, 2022
200 Dec 14, 2022
326 Jan 02, 2023
21 Jun 25, 2022
4.1k Dec 29, 2022
640 Dec 31, 2022
2.3k Jan 05, 2023
2.5k Jan 05, 2023
129 Dec 24, 2022
57 Dec 17, 2022
3.3k Jan 04, 2023
8 May 23, 2022
2 Jan 18, 2022
1 Feb 01, 2022
7k Jan 06, 2023
1 Dec 22, 2021
8 Sep 19, 2022
7.1k Jan 01, 2023