Pinned Repositories
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
kirgush's Repositories
kirgush/18337
18.337 - Parallel Computing and Scientific Machine Learning
kirgush/18S096SciML
18.S096 - Applications of Scientific Machine Learning
kirgush/a3c_trading
Trading with recurrent actor-critic reinforcement learning
kirgush/aa228-notebook
IJulia notebooks for AA228/CS238 Decision Making Under Uncertainty course at Stanford University
kirgush/AD
Light-weight implementation of Algorithmic Differentiation in the Wolfram Language
kirgush/advanced-shiny
Shiny tips & tricks for improving your apps and solving common problems
kirgush/AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.
kirgush/cvxportfolio
Portfolio optimization and simulation in Python
kirgush/cvxpower
Power Network Optimization and Simulation.
kirgush/cvxr_docs
kirgush/cvxr_tutorial
useR! 2019 CVXR tutorial
kirgush/dashboard
Sample codes for creating interactive dashboard for scorecards monitoring
kirgush/feasibility_region
feasibility regions csv
kirgush/flowery
Make R a more flowery language with generators and transducers
kirgush/funneljoin
Join tables based on events occurring in sequence in a funnel.
kirgush/google-research
Google Research
kirgush/gym-anm
Design Reinforcement Learning environments that model Active Network Management (ANM) tasks in electricity distribution networks.
kirgush/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
kirgush/MAgent
A Platform for Many-agent Reinforcement Learning
kirgush/MLCrashCourse
Julia files inspired by Google's Machine Learning Crash Course
kirgush/monitoring_paper
material for paper about models monitoring with R
kirgush/notebooks
Demonstrate, reproduce and extend the results in the article 'Learning The Shape: Differential Machine Learning' (Huge & Savine, Risk 2020), and discuss implementation details
kirgush/rl
Deep Reinforcement Learning For Trading
kirgush/rstudio_conf_2019_eager_execution
kirgush/RStudioConf2019Slides
Links to slides for rstudio::conf 2019
kirgush/SDE
Example codes for the book Applied Stochastic Differential Equations
kirgush/STMO
Selected Topics in Mathematical Optimization, now in Julia
kirgush/stochastic-optimization
Sequential Decision Problem Modeling Library @ Castle Lab, Princeton Univ.
kirgush/tidytuesday
Repo for initial setup of the #tidytuesday visualization project
kirgush/Zero2Hero-JuliaWorkshop
Intensive Julia workshop that takes you from zero to hero