Brendan Hasz

Me
PhD Candidate 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. 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.

Tags

All Posts python r

All Posts

Customer Loyalty Prediction 3: Predictive Modeling
19 Jun 2019 - python and prediction

Performing hyperparameter optimization, and creating ensemble and stacking models to predict customer loyalty.


Bayesian Gaussian Mixture Modeling with Stochastic Variational Inference
12 Jun 2019 - python, bayesian, and tensorflow

How to fit a Bayesian Gaussian mixture model via stochastic variational inference, using TensorFlow Probability and TensorFlow 2.0 eager execution.


Career Village Question Recommendation System
20 May 2019 - python, feature engineering, and recommendation

Joining and aggregating data across multiple tables, and building a content-based implicit reccomendation system to recommend questions asked by students to professionals who can answer them.


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 - python, bayesian, prediction, and optimization

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, data cleaning, 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, eda, prediction, uncertainty, and visualization

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 - python, bayesian, 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 - r, bayesian, and stan

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


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

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


Home Credit Group Loan Risk Prediction
11 Oct 2018 - python, data cleaning, 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 - r, bayesian, and stan

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 - python, eda, and visualization

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


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

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


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

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


Posts in python

Customer Loyalty Prediction 3: Predictive Modeling
19 Jun 2019 - python and prediction

Performing hyperparameter optimization, and creating ensemble and stacking models to predict customer loyalty.


Bayesian Gaussian Mixture Modeling with Stochastic Variational Inference
12 Jun 2019 - python, bayesian, and tensorflow

How to fit a Bayesian Gaussian mixture model via stochastic variational inference, using TensorFlow Probability and TensorFlow 2.0 eager execution.


Career Village Question Recommendation System
20 May 2019 - python, feature engineering, and recommendation

Joining and aggregating data across multiple tables, and building a content-based implicit reccomendation system to recommend questions asked by students to professionals who can answer them.


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 - python, bayesian, prediction, and optimization

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, data cleaning, 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, eda, prediction, uncertainty, and visualization

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 - python, bayesian, 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 - python and feature engineering

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


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

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


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

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


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

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


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

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


Posts in r

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

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 - r, bayesian, and stan

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


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 Gaussian Mixture Modeling with Stochastic Variational Inference
12 Jun 2019 - python, bayesian, and tensorflow

How to fit a Bayesian Gaussian mixture model via stochastic variational inference, using TensorFlow Probability and TensorFlow 2.0 eager execution.


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

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 - python, bayesian, 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 - r, bayesian, and stan

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 - r, bayesian, and stan

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 - python, bayesian, and stan

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


Posts tagged "data cleaning"

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

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


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

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


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, data cleaning, 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, eda, prediction, uncertainty, and visualization

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 - python, eda, and visualization

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


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

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


Posts tagged "feature engineering"

Career Village Question Recommendation System
20 May 2019 - python, feature engineering, and recommendation

Joining and aggregating data across multiple tables, and building a content-based implicit reccomendation system to recommend questions asked by students to professionals who can answer them.


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 - python and feature engineering

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 "optimization"

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

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


Posts tagged "prediction"

Customer Loyalty Prediction 3: Predictive Modeling
19 Jun 2019 - python and prediction

Performing hyperparameter optimization, and creating ensemble and stacking models to predict customer loyalty.


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

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, eda, prediction, uncertainty, and visualization

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, data cleaning, and prediction

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


Posts tagged "recommendation"

Career Village Question Recommendation System
20 May 2019 - python, feature engineering, and recommendation

Joining and aggregating data across multiple tables, and building a content-based implicit reccomendation system to recommend questions asked by students to professionals who can answer them.


Posts tagged "stan"

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

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 - r, bayesian, and stan

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 - python, bayesian, and stan

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


Posts tagged "tensorflow"

Bayesian Gaussian Mixture Modeling with Stochastic Variational Inference
12 Jun 2019 - python, bayesian, and tensorflow

How to fit a Bayesian Gaussian mixture model via stochastic variational inference, using TensorFlow Probability and TensorFlow 2.0 eager execution.


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

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 - python, bayesian, 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 "visualization"

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

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 - python, eda, and visualization

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


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

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