Serdar Yegulalp
Senior Writer
Serdar Yegulalp is a senior writer at InfoWorld, covering software development and operations tools, machine learning, containerization, and reviews of products in those categories. Before joining InfoWorld, Serdar wrote for the original Windows Magazine, InformationWeek, the briefly resurrected Byte, and a slew of other publications. When he's not covering IT, he's writing SF and fantasy published under his own personal imprint, Infinimata Press.
OpenAI debuts Python-based Triton for GPU-powered machine learning
Triton uses Python’s syntax to compile to GPU-native code, without the complexities of GPU programming.
6 stellar libraries for profiling Python code
Get deep insight into where your Python app is slow with these profiling utilities.
6 essential Python tools for data science—now improved
SciPy, Numba, Cython, Dask, Vaex, and Intel SDC all have new versions that aid big data analytics and machine learning projects.
How to use the Python for loop
The for loop construction in Python easily iterates over a collection of items. Here’s what you need to know to use it well.
Rust tutorial: Get started with the Rust language
How to get your feet wet using Rust’s tool chain, creating projects, working with third-party code, and managing libraries.
Speed up your Python with Numba
Want faster number-crunching in Python? You can speed up your existing Python code with the Numba JIT, often with only one instruction.
Get started with Anaconda Python
Anaconda provides a handy GUI, a slew of work environments, and tools to simplify the process of using Python for data science.
Get started with Flask 2.0
Dive head-first into one of the most popular and versatile web frameworks for Python with this quick-start tutorial.
How to use Python’s py launcher for Windows
Take control of multiple Python installations in Windows with the py launcher, available as part of a standard Python installation.
Python’s creators unveil speedup plans for Python
Incremental improvements are on the way that promise to speed up Python by a factor of 2x to 5x, and remain compatible with existing code.
11 tips for speeding up Python programs
Python programmers have many options for improving the performance of their apps. Here’s where to start.
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