100 articles
Marton Trencseni - Mon 18 October 2021 • Tagged with meta
A review and introspect on the first 100 articles written on Bytepawn. 
Cross entropy, joint entropy, conditional entropy and relative entropy
Marton Trencseni - Sat 09 October 2021 • Tagged with entropy, cross-entropy, joint-entropy, conditional-entropy, relative-entropy, kullback–leibler-diverence
What's the difference between cross entropy, joint entropy, conditional entropy and relative entropy? 
What's the entropy of a fair coin toss?
Marton Trencseni - Sat 25 September 2021 • Tagged with entropy, interviews, cross-entropy, physics
What's the entropy of a fair coin toss? What if the coin almost always returns Heads? My recruiter reports that very few candidates can answer these entropy related DS screening questions. 
Five ways to reduce variance in A/B testing
Marton Trencseni - Sun 19 September 2021 • Tagged with ab-testing, variance, stratification, cuped
I use toy Monte Carlo simulations to demonstrate 5 ways to reduce variance in A/B testing: increase sample size, move towards a more even split, reduce variance in the metric definition, stratification and CUPED.
Correlations, seasonality, lift and CUPED
Marton Trencseni - Sun 05 September 2021 • Tagged with ab-testing, cuped
In this final blog post about CUPED, I will address some questions about CUPED, such as, is correlation between "before" and "after" the same as seasonality?
A/A testing and false positives with CUPED
Marton Trencseni - Sun 15 August 2021 • Tagged with ab-testing, cuped
I use Monte Carlo simulations of A/A tests to demonstrate how Data Scientists can incorrectly skew lift and p-values if they pick-and-choose between reporting traditional and CUPED results after the experiment has concluded.
Reducing variance in conversion A/B testing with CUPED
Marton Trencseni - Sat 07 August 2021 • Tagged with ab-testing, cuped
I use Monte Carlo simulations of conversion A/B tests to demonstrate how CUPED reduces measurement variance in conversion experiments.
Reducing variance in A/B testing with CUPED
Marton Trencseni - Sat 31 July 2021 • Tagged with ab-testing, cuped
I use Monte Carlo simulations of A/B tests to demonstrate CUPED, a method to use historic "before" data to reduce the variance in the measurement of the treatment lift.
A/B testing and the historic lift paradox [redacted]
Marton Trencseni - Sun 25 July 2021 • Tagged with redacted
I show how looking at historic "before" values in A/B testing can lead to an apparent paradox.
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, without blocking on external help from other roles?
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.
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.
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. 
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. 
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. 
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.
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.
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?
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.
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.
