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
An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt
Regularization and Feature Selection in Least Squares Temporal Difference Learning Description This is Python implementations of Least Angle Regressio
Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern
🌄 Scalecast: Dynamic Forecasting at Scale About This package uses a scaleable forecasting approach in Python with common scikit-learn and statsmodels
Repository Status for Scikit-learn Live webpage Auto updating website that tracks closed & open issues/PRs on scikit-learn/scikit-learn. Running local
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in
Bayesian Modeling and Computation in Python Open access and Code This repository contains the open access version of the text and the code examples in
A linear equation solver using gaussian elimination. Implemented for fun and learning/teaching. The solver will solve equations of the type: A can be
Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco
Data Science on AWS - O'Reilly Book Get the book on Amazon.com Book Outline Quick Start Workshop (4-hours) In this quick start hands-on workshop, you
The project's goal is to show a real world application of image segmentation using k means algorithm
Tangram Website | Discord Tangram makes it easy for programmers to train, deploy, and monitor machine learning models. Run tangram train to train a mo
Decision Weights in Prospect Theory It's clear that humans are irrational, but how irrational are they? After some research into behavourial economics
climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works
matrixprofile-ts matrixprofile-ts is a Python 2 and 3 library for evaluating time series data using the Matrix Profile algorithms developed by the Keo
implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map,
img2palette Turning images into '9-pan' palettes using KMeans clustering from sklearn. Requirements We require: Pillow, for opening and processing ima
ai-webshell-detect 机器学习检测webshell,利用textcnn+简单二分类网络,基于keras,花了七天 检测原理: 从文件熵 文件长度 文件语句提取出特征,然后文件熵与长度送入二分类网络,文件语句送入textcnn 项目原理,介绍,怎么做出来的
CML with cloud compute This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance
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