Migrating blog from a complex and very manual setup to a more flexible solution

Brief notes and summaries of the most interesting talks from the conference

Building machine learning models in a way that does not drive you crazy

Guidelines on structuring error processing in Python derived from personal experience

Analyzing the results of 2019 Kaggle's Survey among its members about their levels of education, jobs, and salaries

A simple solution to the Career Con 2019 data competition using PyTorch

Analysing the results of a failed coding interview for a Data Scientist position

Performance benchmark for different binary formats to store pandas data frames

A simple, generic implementation of a deep learning training loop in plain PyTorch

An application of a simple neural network based recommendation system to the MovieLens dataset

Implementing a simple version of Random Forest algorithm to classify vectors

An example of using clustering to quantize a continuous dataset into a fixed-size feature vectors

Using Keras and pre-trained deep learning models to classify dog breeds

A powerful conception of gradually consumed streams of data in Python

Using Python magic to replace class implementation dynamically

Notes about building a devbox for local deep learning experiments