hosshonarvar

SegNet

Image segmentation

datasciencecoursera

A repository that will be linked with RStudio

datasharing

The Leek group guide to data sharing

deep-review

A collaboratively written review paper on deep learning, genomics, and precision medicine

EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

homemadeai.co

releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

RTS

Real-time trading simulator

sampleproject

A sample project that exists for PyPUG's "Tutorial on Packaging and Distributing Projects"

tradingview-interactive-brokers

TradingView Interactive Brokers Integration using Webhooks

hosshonarvar/homemadeai.co

hosshonarvar/tradingview-interactive-brokers

TradingView Interactive Brokers Integration using Webhooks

hosshonarvar/sampleproject

A sample project that exists for PyPUG's "Tutorial on Packaging and Distributing Projects"

hosshonarvar/SegNet

Image segmentation

hosshonarvar/EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

hosshonarvar/releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

hosshonarvar/deep-review

A collaboratively written review paper on deep learning, genomics, and precision medicine

hosshonarvar/datasciencecoursera

A repository that will be linked with RStudio

hosshonarvar/datasharing

The Leek group guide to data sharing

hosshonarvar/RTS

Real-time trading simulator