Bytepawn - Marton Trencseni

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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