About This Site

A concise overview of my work: selected projects, technical writing, and open-source contributions.

If you're hiring or exploring collaboration, start with Projects and Resume.

Navigating the Site

Explore the various sections to learn more about my work and expertise:

My blog is categorized into various topics to help you find the information you are interested in. Below are the main categories available:

Algorithms and Data Structures: definitions of common algorithms (sorting, searching, graph) and data structures (lists, trees, hashes) with code examples.
Numerical Methods: algorithms for root finding, integration, differential equations, with step-by-step implementations.
Statistics Notes: explanations of probability distributions, hypothesis tests, regression techniques, illustrated by sample datasets.
Stanford Machine Learning: organized lecture notes covering linear/logistic regression, neural networks, support vector machines, with sample code.
Numpy Tutorials: examples of array creation, indexing, broadcasting, linear algebra routines and performance tips.
Parallel and Concurrent Programming: discussion of threads, processes, synchronization (mutexes, semaphores), and example programs.
Frontend Notes: notes on DOM manipulation, CSS layouts, event handling and basic performance debugging.
Database Notes: SQL examples for table design, joins, indexing, transactions, plus tips for MySQL/PostgreSQL.
Git Notes: common commands (clone, commit, branch, merge), branching strategies and conflict resolution examples.
Linux Notes: shell commands, file permissions, package management and basic scripting examples.
VTK Examples: code snippets for 3D rendering, mesh handling, volume visualization and scene setup.

Kurs Podstaw Pythona: omówienie składni, typów danych, instrukcji sterujących, funkcji i podstawowych bibliotek z przykładami.
Od C do C++: porównanie składni C i C++, przykłady obiektowości, szablonów i użycia standardowej biblioteki STL.