The Full Stack Data Scientist

Marton Trencseni - Fri 23 July 2021 • Tagged with data, fallacies

What are the core skills a data scientist needs to sustainably achieve bottom-line impact?

Data Scientist

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Comparing NeuralProphet and Prophet for timeseries forecasting

Marton Trencseni - Tue 20 July 2021 • Tagged with modeling, timeseries, prophet, neuralprophet

I compare Prophet and NeuralProphet performance using a toy forecasting benchmark.

NeuralProphet

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Timeseries forecasting with Prophet

Marton Trencseni - Sun 18 July 2021 • Tagged with modeling, timeseries, prophet

Prophet is a simple to use timeseries forecasting library by Facebook.

Prophet

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YOLO object detection architecture

Marton Trencseni - Sat 10 July 2021 • Tagged with yolo, yolov5, vision, object detection

I discuss the YOLO neural network architecture for object detection.

YOLO architecture

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YOLOv5 object detection experiments

Marton Trencseni - Fri 02 July 2021 • Tagged with yolo, yolov5, vision, object detection

I run object detection experiments with pre-trained YOLOv5 models.

YOLO object detection example

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Predicting party affiliation of US politicians using fasttext

Marton Trencseni - Sun 20 June 2021 • Tagged with statistics, trump, politics, fasttext, twitter

I train a fasttext classifier on 1.2M data points to predict US politicians' party affiliations from their twitter messages.

Trump Schiff

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Random digits and Benford's law

Marton Trencseni - Sat 29 May 2021 • Tagged with statistics

The post explores the distribution of digits of random and non-random numbers from receipts, verifying Benford's law of first digit distribution.

Early stopping

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Tricks vs implementation in coding interviews

Marton Trencseni - Sat 22 May 2021 • Tagged with hiring, interviewing

Thinking up tricky solutions in 3-5 minutes is not a requirement in a work setting. Usually, there are days or weeks for that. But implementing an idea, once the idea is there, should be straightforward for a good programmer.

Daily Coding Problem

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10 ways to iterate from 0 to 1 with deciles

Marton Trencseni - Fri 14 May 2021 • Tagged with mlflow, tracking

What's the best way to iteratore from 0 to 1 in steps of 0.1 in Python, and what are the potential pitfalls?

Iterating from 0 to 1 in steps of 0.1

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Sometimes brute forcing just works

Marton Trencseni - Thu 06 May 2021 • Tagged with python

I describe a real world use-case where a simple, brute force search based solution worked really well, making more sophisticated Machine Learning unnecessary.

Sample receipt

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Building intuition for p-values and statistical significance

Marton Trencseni - Sun 25 April 2021 • Tagged with ab-testing

This is the transcript of a talk I did on experimentation and A/B testing, to give the audience an intuitive understanding of p-values and statistical significance.

Coin flip

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Random numbers, the natural logarithm and higher dimensional simplexes

Marton Trencseni - Sat 17 April 2021 • Tagged with bayesian, ab-test

The base $e$ of the natural logarithm shows up in an unexpected place. Let's derive why!

Simplex

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Classification accuracy of quantized Autoencoders with Pytorch and MNIST

Marton Trencseni - Fri 09 April 2021 • Tagged with python, pytorch, cnn, torchvision, mnist, autoencoder

I measure how the classification accuracy of quantized Autoencoder neural network varies with encoding bits on MNIST digits.

Classifier accuracy on quantized Autoencoder output after quantization

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Investigating information storage in quantized Autoencoders with Pytorch and MNIST

Marton Trencseni - Sun 04 April 2021 • Tagged with python, pytorch, cnn, torchvision, mnist, autoencoder

I investigate how much information an Autoencoder neural network encodes for MNIST digits.

Pytorch Autoencoder loss with encoding dimension and quantization bits

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Building a Pytorch Autoencoder for MNIST digits

Marton Trencseni - Thu 18 March 2021 • Tagged with pytorch, autoencoder, mnist

I build an Autoencoder network to categorize MNIST digits in Pytorch.

Conversion difference vs N

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The best parts of Invent and Wander: the Collected Writings of Jeff Bezos

Marton Trencseni - Sat 06 March 2021 • Tagged with business, experimentation

These are the best parts from the book "Invent and Wander: the Collected Writings of Jeff Bezos". The book is a collection of the annual Amazon shareholder letters that Jeff Bezos has been sending out since 1997, and speeches he has given over time.

Jeff Bezos Invent and Wander

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Training a Pytorch Wasserstein MNIST GAN on Google Colab

Marton Trencseni - Wed 03 March 2021 • Tagged with ab-testing

I train a Pytorch Wasserstein MNIST GAN on Google Colab to beautiful MNIST digits.

Wasserstein GAN Generated MNIST digits

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Training a Pytorch Classic MNIST GAN on Google Colab

Marton Trencseni - Tue 02 March 2021 • Tagged with ab-testing

I train a Pytorch Classic MNIST GAN on Google Colab to generate MNIST digits.

Classic GAN Generated MNIST digits

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How I manage notifications to keep myself uninterrupted

Marton Trencseni - Mon 22 February 2021 • Tagged with personal, interruptions, notifications

I love using apps, email, social networking and messaging. But I want to do use them on my own time. So many years ago I decided to not let my phone interrupt me.

My phone's lock screen

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Training a Pytorch Lightning MNIST GAN on Google Colab

Marton Trencseni - Sat 20 February 2021 • Tagged with python, pytorch, gan, mnist, google-colab

I explore MNIST digits generated by a Generative Adversarial Network trained on Google Colab using Pytorch Lightning.

Softmax GAN after 5 epoch, 100 samples.

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