dpalpha

dcherevyk's starred repositories

pycaleva

A framework for calibration measurement of binary probabilistic models

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auto-sklearn

Automated Machine Learning with scikit-learn

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In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

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scorecard

Scorecard Development in R, 评分卡

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gretl_teamB

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skimr

:exclamation: This is a read-only mirror of the CRAN R package repository. skimr — Compact and Flexible Summaries of Data. Homepage: https://docs.ropensci.org/skimr/ (website), https://github.com/ropensci/skimr/ Report bugs for this package: https://github.com/ropensci/skimr/issues

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deap

Distributed Evolutionary Algorithms in Python

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xtbreak

Testing and Estimation of structural breaks in Stata

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mojo

The Mojo Programming Language

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MS-DOS

The original sources of MS-DOS 1.25, 2.0, and 4.0 for reference purposes

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WALKOFF

A flexible, easy to use, automation framework allowing users to integrate their capabilities and devices to cut through the repetitive, tedious tasks slowing them down. #nsacyber

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Evolutionary-Optimization

A generic evolutionary algorithm for function optimisation.

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End-to-End-Data-Science

Code repository for the End-to-End Data Science in SAS book

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ifrs9

The full scope of IFRS 9 Impairment models including PD, LGD and EAD are provided. It also covers ECL, which is the combination of those three parameters as well as staging criteria.

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big_data_project_pw

The final project for Big Data PW post-graduate studies

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EqVariance

A variance swap is an instrument which allows investors to trade future realized (historical) volatility against current implied volatility. The Variance Swap pays the difference between observed variance and a strike variance, possibly subject to a cap and a floor. The observed variance is computed from the stock price returns over a series of specified sampling dates.

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