kirgush Goto Github PK

18337

18.337 - Parallel Computing and Scientific Machine Learning

18s096sciml

18.S096 - Applications of Scientific Machine Learning

a3c_trading

Trading with recurrent actor-critic reinforcement learning

aa228-notebook

IJulia notebooks for AA228/CS238 Decision Making Under Uncertainty course at Stanford University

ad

Light-weight implementation of Algorithmic Differentiation in the Wolfram Language

advanced-shiny

Shiny tips & tricks for improving your apps and solving common problems

alphazero.jl

A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.

barrieroption

blogr

.Rmd files for blogR

cvxportfolio

Portfolio optimization and simulation in Python

cvxpower

Power Network Optimization and Simulation.

cvxr_docs

cvxr_tutorial

useR! 2019 CVXR tutorial

dashboard

Sample codes for creating interactive dashboard for scorecards monitoring

deep-learning-with-r-notebooks

R notebooks for the code samples of the book "Deep Learning with R"

feasibility_region

feasibility regions csv

flowery

Make R a more flowery language with generators and transducers

funneljoin

Join tables based on events occurring in sequence in a funnel.

google-research

Google Research

gym-anm

Design Reinforcement Learning environments that model Active Network Management (ANM) tasks in electricity distribution networks.

ipython_notebooks

Set of Jupyter (iPython) notebooks (and few pdf-presentations) about things that I am interested on, like Computer Science, Statistics and Machine-Learning, Artificial Intelligence (AI), Financial Engineering, Optimization, Stochastic Modelling, Time-Series forecasting, Science in general... and more.

leastsquaresmontecarlomodels

longstaff-schwartz_model

Implementation of the Longstaff-Schwartz term structure model

machine-learning-under-optimization-lens-fall2018

Work from class 15.095 Machine Learning Under a Modern Optimization Lens at MIT taught by Dimitris Bertsimas and Martin Copenhaver

magent

A Platform for Many-agent Reinforcement Learning

mlcrashcourse

Julia files inspired by Google's Machine Learning Crash Course

mlwithjulia

Julia code snippets to help with general machine learning algorithm implementations. Based on Andrew Ng ML course on coursera.

monitoring_paper

material for paper about models monitoring with R

notebooks

Demonstrate, reproduce and extend the results in the article 'Learning The Shape: Differential Machine Learning' (Huge & Savine, Risk 2020), and discuss implementation details

optlng