A new way to build a blog
Migrating blog from a complex and very manual setup to a more flexible solution
PyCon & PyData Berlin 2022: Notes in the Margin
Brief notes and summaries of the most interesting talks from the conference
Stress-Free Machine Learning
Building machine learning models in a way that does not drive you crazy
Python Errors Done Right
Guidelines on structuring error processing in Python derived from personal experience
Education, Title, Salary: How Are They Related?
Analyzing the results of 2019 Kaggle's Survey among its members about their levels of education, jobs, and salaries
Time Series Classification with PyTorch
A simple solution to the Career Con 2019 data competition using PyTorch
How to Fail a Coding Interview
Analysing the results of a failed coding interview for a Data Scientist position
The Best Format to Save Pandas Data Frame
Performance benchmark for different binary formats to store pandas data frames
Deep Learning Model Training Loop
A simple, generic implementation of a deep learning training loop in plain PyTorch
Building Simple Recommendation System with PyTorch
An application of a simple neural network based recommendation system to the MovieLens dataset
Classifying Quantized Dataset with Random Forest Classifier (Part 2)
Implementing a simple version of Random Forest algorithm to classify vectors
Using K-Means Clustering to Quantize Dataset Samples (Part 1)
An example of using clustering to quantize a continuous dataset into a fixed-size feature vectors
Dogs Breeds Classification with Keras
Using Keras and pre-trained deep learning models to classify dog breeds
Generators-Based Data Processing Pipeline
A powerful conception of gradually consumed streams of data in Python
Using Python's __new__ Method to Dynamically Switch Class Implementations
Using Python magic to replace class implementation dynamically
Deep Learning Machine Software: Ubuntu, CUDA, and TensorFlow
Notes about building a devbox for local deep learning experiments