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6 programming languages that sound fake but aren’t
No fake news here, you really can program with musical notes if you want to!
Suppose you are working on a complex bash script to automate a series of tasks on your Linux system. You notice that as it grows, there are certain parts of the script where the same code blocks are ...
Official support for free-threaded Python, and free-threaded improvements Python’s free-threaded build promises true parallelism for threads in Python programs by removing the Global Interpreter Lock ...
Community driven content discussing all aspects of software development from DevOps to design patterns. Ready to develop your first AWS Lambda function in Python? It really couldn’t be easier. The AWS ...
Functions are the building blocks of Python programming. They let you organize your code, reduce repetition, and make your programs more readable and reusable. Whether you’re writing small scripts or ...
Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...
https://www.riteshmodi.com - Data Scientist, AI and blockchain expert with proven open-source solutions on MLOps, LLMOps and GenAIOps. https://www.riteshmodi.com - Data Scientist, AI and blockchain ...
What if the tools you already use could do more than you ever imagined? Picture this: you’re working on a massive dataset in Excel, trying to make sense of endless rows and columns. It’s slow, ...
Q. Could you explain how the AGGREGATE function works in Excel? A. AGGREGATE is possibly the most versatile function in Excel. Think of it as an advanced version of the SUBTOTAL function that offers ...
Abstract: The problem of straggler mitigation in distributed matrix multiplication (DMM) is considered for a large number of worker nodes and a fixed small finite field. Polynomial codes and matdot ...
Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.
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