Series Path · 11 parts
Python for ML Engineers
Python language features, tooling, and Rust extensions every ML engineer should know — decorators, functools, itertools, concurrency, Python 3.14, Rust, data tooling, and metric visualization.
Curriculum — 11 parts
- 01
Python Decorators: A Complete Guide with Useful Examples
Python decorators are one of the most powerful and elegant features of the language. They allow you to modify or enhance the behavior of functions, methods, or…
5 min read - 02
Complete Guide to Python’s functools Module
The functools module in Python provides utilities for working with higher-order functions and operations on callable objects. It’s a powerful toolkit for…
13 min read - 03
Complete Guide to Python’s itertools Module
The itertools module is one of Python’s most powerful standard library modules for creating iterators and performing functional programming operations. It…
18 min read - 04
Python Multiprocessing and Multithreading: A Comprehensive Guide
Python provides two primary approaches for concurrent execution: multithreading and multiprocessing. Understanding when and how to use each is crucial for…
18 min read - 05
Python 3.14: The Next Evolution in Python Development
Python continues its steady march forward with the anticipated release of Python 3.14, marking another significant milestone in the language’s evolution. As…
3 min read - 06
Python 3.14: Key Improvements and New Features
Python 3.14 introduces several significant improvements focused on performance, developer experience, and language capabilities. This guide covers the most…
6 min read - 07
Getting Started with Rust: A Complete Guide
Rust is a systems programming language that focuses on safety, speed, and concurrency. It prevents common programming errors like null pointer dereferences and…
6 min read - 08
Python Package Development with Rust - Complete Guide
This guide covers creating Python packages with Rust backends using PyO3 and maturin. This approach combines Rust’s performance and safety with Python’s…
8 min read - 09
From Pandas to Polars
As datasets grow in size and complexity, performance and efficiency become critical in data processing. While Pandas has long been the go-to library for data…
9 min read - 10
Python Data Visualization: Matplotlib vs Seaborn vs Altair
This guide compares three popular Python data visualization libraries: Matplotlib, Seaborn, and Altair (Vega-Altair). Each library has its own strengths,…
9 min read - 11
A Beginner’s Guide to Metric Visualization
From TensorBoard to MLflow
21 min read