Richard Michael – Medium

Richard Michael

Richard Michael
in
Towards Data Science

Infinitely Wide Neural-Networks | Neural Tangents Explained

use Python and JAX to efficiently build infinitely wide networks for deeper network insights on your finite machine.

11 min readDec 14, 2020

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Infinitely Wide Neural-Networks | Neural Tangents Explained

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Richard Michael
in
Towards Data Science

Optimizing Hyperparameters the right Way

Efficiently exploring the parameter-search through Bayesian Optimization with skopt in Python. TL;DR: my hyperparameters are always better…

7 min readSep 30, 2020

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Optimizing Hyperparameters the right Way

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Richard Michael
in
Towards Data Science

Millennial Suicides — an Analysis about Change

A simple, yet meaningful Pyro model to uncover change-points over time.

6 min readAug 5, 2020

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Millennial Suicides — an Analysis about Change

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Richard Michael
in
Towards Data Science

Improve Your Model with Missing Data | Imputation with NumPyro

Make the best of missing data the Bayesian way. Improve model performance and make comparative benchmarks using Monte Carlo methods.

9 min readJul 28, 2020

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Improve Your Model with Missing Data | Imputation with NumPyro

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Richard Michael
in
Towards Data Science

3 Probabilistic Frameworks You should know | The Bayesian Toolkit

Build better Data Science workflows with probabilistic programming languages and counter the shortcomings of classical ML.

4 min readJul 20, 2020

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3 Probabilistic Frameworks You should know | The Bayesian Toolkit

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Richard Michael
in
Towards Data Science

Single-Parameter Models | Pyro vs. STAN

Modeling U.S. cancer-death rates with two Bayesian approaches: MCMC in STAN and SVI in Pyro.

8 min readJul 15, 2020

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Single-Parameter Models | Pyro vs. STAN

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Richard Michael
in
Towards Data Science

10.000 hours in Data Science | Gaining Proficiency

The way from data novice to professional.

7 min readJun 26, 2020

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10.000 hours in Data Science | Gaining Proficiency

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Richard Michael
in
Towards Data Science

Compute the Incomputable | How SVI and ELBO work

One reason why Bayesian Modeling works with real world data. The approximate light-house in the sea of randomness.

8 min readJun 22, 2020

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Compute the Incomputable | How SVI and ELBO work

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Richard Michael
in
Towards Data Science

How your model is optimized | Know your Optimization

The answer to: “Why is my model running forever?” or the classic: “I think it might have converged?”

8 min readJun 15, 2020

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How your model is optimized | Know your Optimization

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Richard Michael
in
Towards Data Science

Pyro Top-Down Forecasting | Application-case

Connect the dots over time and forecast with confidence(-intervals).

9 min readJun 8, 2020

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Pyro Top-Down Forecasting | Application-case

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Richard Michael

Richard Michael

I am a Data Scientist and M.Sc. student in Bioinformatics at the University of Copenhagen. You can find more content on my weekly blog http://laplaceml.com/blog

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