Brendan Hasz

Me
PhD Student in Neuroscience at
Minneapolis, MN

Hi! I'm a PhD Student in Neuroscience at the University of Minnesota. I research the neural mechanisms behind habitual and deliberative decision-making in the lab of David Redish. Currently I'm recording from neurons in the hippocampus and prefrontal cortex of rats as they run through mazes, and determining how those areas encode information about contingencies, reward, and choice. I'm also interested in data science and machine learning - especially in accurately quantifying the uncertainty of predictive models.

On the side, I'm working on ProbFlow, a Python package for Bayesian modeling.

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All Posts

Customer Loyalty Prediction 2: Feature Engineering and Feature Selection
04 Apr 2019 - python, feature engineering, and feature selection

Engineering features, performing aggregations with transaction information, and using mutual information and permutation-based feature importance to select features.


Bayesian Hyperparameter Optimization using Gaussian Processes
28 Mar 2019 - bayesian, python, and prediction

Finding the best hyperparameters for a predictive model in an automated way using Bayesian optimization.


Customer Loyalty Prediction 1: Data Cleaning and EDA
20 Mar 2019 - python and eda

Data loading, cleaning, and exploratory data analysis for the Elo customer loyalty prediction challenge.


Representing Categorical Data with Target Encoding
04 Mar 2019 - python and prediction

Representing categorical variables with high cardinality using target encoding, and mitigating overfitting often seen with target encoding by using cross-fold and leave-one-out schemes.


Documenting Python Packages with Sphinx and ReadTheDocs
05 Jan 2019 - python and tools

Writing and generating documentation for python packages using Sphinx, and hosting and automatically building the documentation with ReadTheDocs.


Prediction Intervals for Taxi Fares using Quantile Loss
15 Dec 2018 - python, uncertainty, prediction, and eda

Training gradient boosted decision trees with a quantile loss to predict taxi fares, in python using catboost and vaex.


Bayesian Regressions with MCMC or Variational Bayes using TensorFlow Probability
03 Dec 2018 - bayesian, python, tensorflow, and uncertainty

Bayesian regressions via MCMC sampling or variational inference using TensorFlow Probability, a new package for probabilistic model-building and inference.


Multilevel Gaussian Processes and Hidden Markov Models with Stan
15 Nov 2018 - bayesian, stan, and r

Multilevel and multitrial Gaussian Processes and hidden Markov models in R, using Stan and bridge sampling.


Automated Feature Engineering with Featuretools
11 Nov 2018 - feature engineering, featuretools, and python

Running deep feature synthesis for automated feature engineering, using the Featuretools package for Python.


Home Credit Group Loan Risk Prediction
11 Oct 2018 - python and prediction

Prediction of loan default using python, scikit-learn, and XGBoost.


Bayesian Modeling of Gaussian Processes and Hidden Markov Models with Stan
10 Oct 2018 - bayesian, stan, and r

Model comparison between Bayesian fits of Gaussian Processes and hidden Markov models in R, using Stan and bridge sampling.


Running a Docker Container on AWS EC2
30 Aug 2018 - aws, docker, and tools

How to set up an AWS account, launch an instance, run a docker container in that instance, and upload/download data to and from the container.


Nice Ride Bike Share EDA
02 Aug 2018 - eda, python, and bokeh

Exploratory data analysis of Nice Ride MN bike share's system data for 2017.


Fatal Police Shootings EDA
08 Jul 2018 - eda, python, and bokeh

Exploratory data analysis of the Washington Post's database of fatal police shootings in the US since 2015.


Multilevel Bayesian Correlations
27 Jun 2018 - bayesian, stan, and python

Fitting Bayesian models of the correlation between two variables to data with multiple observations per subject or group. Using Stan!


Posts tagged "aws"

Running a Docker Container on AWS EC2
30 Aug 2018 - aws, docker, and tools

How to set up an AWS account, launch an instance, run a docker container in that instance, and upload/download data to and from the container.


Posts tagged "bayesian"

Bayesian Hyperparameter Optimization using Gaussian Processes
28 Mar 2019 - bayesian, python, and prediction

Finding the best hyperparameters for a predictive model in an automated way using Bayesian optimization.


Bayesian Regressions with MCMC or Variational Bayes using TensorFlow Probability
03 Dec 2018 - bayesian, python, tensorflow, and uncertainty

Bayesian regressions via MCMC sampling or variational inference using TensorFlow Probability, a new package for probabilistic model-building and inference.


Multilevel Gaussian Processes and Hidden Markov Models with Stan
15 Nov 2018 - bayesian, stan, and r

Multilevel and multitrial Gaussian Processes and hidden Markov models in R, using Stan and bridge sampling.


Bayesian Modeling of Gaussian Processes and Hidden Markov Models with Stan
10 Oct 2018 - bayesian, stan, and r

Model comparison between Bayesian fits of Gaussian Processes and hidden Markov models in R, using Stan and bridge sampling.


Multilevel Bayesian Correlations
27 Jun 2018 - bayesian, stan, and python

Fitting Bayesian models of the correlation between two variables to data with multiple observations per subject or group. Using Stan!


Posts tagged "bokeh"

Nice Ride Bike Share EDA
02 Aug 2018 - eda, python, and bokeh

Exploratory data analysis of Nice Ride MN bike share's system data for 2017.


Fatal Police Shootings EDA
08 Jul 2018 - eda, python, and bokeh

Exploratory data analysis of the Washington Post's database of fatal police shootings in the US since 2015.


Posts tagged "docker"

Running a Docker Container on AWS EC2
30 Aug 2018 - aws, docker, and tools

How to set up an AWS account, launch an instance, run a docker container in that instance, and upload/download data to and from the container.


Posts tagged "eda"

Customer Loyalty Prediction 1: Data Cleaning and EDA
20 Mar 2019 - python and eda

Data loading, cleaning, and exploratory data analysis for the Elo customer loyalty prediction challenge.


Prediction Intervals for Taxi Fares using Quantile Loss
15 Dec 2018 - python, uncertainty, prediction, and eda

Training gradient boosted decision trees with a quantile loss to predict taxi fares, in python using catboost and vaex.


Nice Ride Bike Share EDA
02 Aug 2018 - eda, python, and bokeh

Exploratory data analysis of Nice Ride MN bike share's system data for 2017.


Fatal Police Shootings EDA
08 Jul 2018 - eda, python, and bokeh

Exploratory data analysis of the Washington Post's database of fatal police shootings in the US since 2015.


Posts tagged "feature engineering"

Customer Loyalty Prediction 2: Feature Engineering and Feature Selection
04 Apr 2019 - python, feature engineering, and feature selection

Engineering features, performing aggregations with transaction information, and using mutual information and permutation-based feature importance to select features.


Automated Feature Engineering with Featuretools
11 Nov 2018 - feature engineering, featuretools, and python

Running deep feature synthesis for automated feature engineering, using the Featuretools package for Python.


Posts tagged "feature selection"

Customer Loyalty Prediction 2: Feature Engineering and Feature Selection
04 Apr 2019 - python, feature engineering, and feature selection

Engineering features, performing aggregations with transaction information, and using mutual information and permutation-based feature importance to select features.


Posts tagged "featuretools"

Automated Feature Engineering with Featuretools
11 Nov 2018 - feature engineering, featuretools, and python

Running deep feature synthesis for automated feature engineering, using the Featuretools package for Python.


Posts tagged "prediction"

Bayesian Hyperparameter Optimization using Gaussian Processes
28 Mar 2019 - bayesian, python, and prediction

Finding the best hyperparameters for a predictive model in an automated way using Bayesian optimization.


Representing Categorical Data with Target Encoding
04 Mar 2019 - python and prediction

Representing categorical variables with high cardinality using target encoding, and mitigating overfitting often seen with target encoding by using cross-fold and leave-one-out schemes.


Prediction Intervals for Taxi Fares using Quantile Loss
15 Dec 2018 - python, uncertainty, prediction, and eda

Training gradient boosted decision trees with a quantile loss to predict taxi fares, in python using catboost and vaex.


Home Credit Group Loan Risk Prediction
11 Oct 2018 - python and prediction

Prediction of loan default using python, scikit-learn, and XGBoost.


Posts tagged "python"

Customer Loyalty Prediction 2: Feature Engineering and Feature Selection
04 Apr 2019 - python, feature engineering, and feature selection

Engineering features, performing aggregations with transaction information, and using mutual information and permutation-based feature importance to select features.


Bayesian Hyperparameter Optimization using Gaussian Processes
28 Mar 2019 - bayesian, python, and prediction

Finding the best hyperparameters for a predictive model in an automated way using Bayesian optimization.


Customer Loyalty Prediction 1: Data Cleaning and EDA
20 Mar 2019 - python and eda

Data loading, cleaning, and exploratory data analysis for the Elo customer loyalty prediction challenge.


Representing Categorical Data with Target Encoding
04 Mar 2019 - python and prediction

Representing categorical variables with high cardinality using target encoding, and mitigating overfitting often seen with target encoding by using cross-fold and leave-one-out schemes.


Documenting Python Packages with Sphinx and ReadTheDocs
05 Jan 2019 - python and tools

Writing and generating documentation for python packages using Sphinx, and hosting and automatically building the documentation with ReadTheDocs.


Prediction Intervals for Taxi Fares using Quantile Loss
15 Dec 2018 - python, uncertainty, prediction, and eda

Training gradient boosted decision trees with a quantile loss to predict taxi fares, in python using catboost and vaex.


Bayesian Regressions with MCMC or Variational Bayes using TensorFlow Probability
03 Dec 2018 - bayesian, python, tensorflow, and uncertainty

Bayesian regressions via MCMC sampling or variational inference using TensorFlow Probability, a new package for probabilistic model-building and inference.


Automated Feature Engineering with Featuretools
11 Nov 2018 - feature engineering, featuretools, and python

Running deep feature synthesis for automated feature engineering, using the Featuretools package for Python.


Home Credit Group Loan Risk Prediction
11 Oct 2018 - python and prediction

Prediction of loan default using python, scikit-learn, and XGBoost.


Nice Ride Bike Share EDA
02 Aug 2018 - eda, python, and bokeh

Exploratory data analysis of Nice Ride MN bike share's system data for 2017.


Fatal Police Shootings EDA
08 Jul 2018 - eda, python, and bokeh

Exploratory data analysis of the Washington Post's database of fatal police shootings in the US since 2015.


Multilevel Bayesian Correlations
27 Jun 2018 - bayesian, stan, and python

Fitting Bayesian models of the correlation between two variables to data with multiple observations per subject or group. Using Stan!


Posts tagged "r"

Multilevel Gaussian Processes and Hidden Markov Models with Stan
15 Nov 2018 - bayesian, stan, and r

Multilevel and multitrial Gaussian Processes and hidden Markov models in R, using Stan and bridge sampling.


Bayesian Modeling of Gaussian Processes and Hidden Markov Models with Stan
10 Oct 2018 - bayesian, stan, and r

Model comparison between Bayesian fits of Gaussian Processes and hidden Markov models in R, using Stan and bridge sampling.


Posts tagged "stan"

Multilevel Gaussian Processes and Hidden Markov Models with Stan
15 Nov 2018 - bayesian, stan, and r

Multilevel and multitrial Gaussian Processes and hidden Markov models in R, using Stan and bridge sampling.


Bayesian Modeling of Gaussian Processes and Hidden Markov Models with Stan
10 Oct 2018 - bayesian, stan, and r

Model comparison between Bayesian fits of Gaussian Processes and hidden Markov models in R, using Stan and bridge sampling.


Multilevel Bayesian Correlations
27 Jun 2018 - bayesian, stan, and python

Fitting Bayesian models of the correlation between two variables to data with multiple observations per subject or group. Using Stan!


Posts tagged "tensorflow"

Bayesian Regressions with MCMC or Variational Bayes using TensorFlow Probability
03 Dec 2018 - bayesian, python, tensorflow, and uncertainty

Bayesian regressions via MCMC sampling or variational inference using TensorFlow Probability, a new package for probabilistic model-building and inference.


Posts tagged "tools"

Documenting Python Packages with Sphinx and ReadTheDocs
05 Jan 2019 - python and tools

Writing and generating documentation for python packages using Sphinx, and hosting and automatically building the documentation with ReadTheDocs.


Running a Docker Container on AWS EC2
30 Aug 2018 - aws, docker, and tools

How to set up an AWS account, launch an instance, run a docker container in that instance, and upload/download data to and from the container.


Posts tagged "uncertainty"

Prediction Intervals for Taxi Fares using Quantile Loss
15 Dec 2018 - python, uncertainty, prediction, and eda

Training gradient boosted decision trees with a quantile loss to predict taxi fares, in python using catboost and vaex.


Bayesian Regressions with MCMC or Variational Bayes using TensorFlow Probability
03 Dec 2018 - bayesian, python, tensorflow, and uncertainty

Bayesian regressions via MCMC sampling or variational inference using TensorFlow Probability, a new package for probabilistic model-building and inference.