How-To Geek on MSN

Generate realistic test data in Python fast. No dataset required

Learn the NumPy trick for generating synthetic data that actually behaves like real data.
CNX Software

Raspberry Pi AI HAT+ 2 review – A 40 TOPS AI accelerator tested with Computer Vision, LLM, and VLM workloads

Raspberry Pi sent me a sample of their AI HAT+ 2 generative AI accelerator based on Hailo-10H for review. The 40 TOPS AI ...
Asianet Newsable on MSN

Best AI and data science courses for workflow automation

To help professionals build these capabilities, we have curated a list of the best applied AI and data science courses.
IEEE

Productivity, Portability, Performance, and Reproducibility: Data-Centric Python

Abstract: Python has become the de facto language for scientific computing. Programming in Python is highly productive, mainly due to its rich science-oriented software ecosystem built around the ...
C&EN

Modular Integration of Python Programming in Undergraduate Physical Chemistry Experiments

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Programming is a key transferable skill within the chemical sciences with applications ...
C&EN

Acceleration of the Relativistic Dirac–Kohn–Sham Method with GPU: A Pre-Exascale Implementation of BERTHA and PyBERTHA

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this paper, we present the recent advances in the computation of the ...
GitHub

Numpy--random module in numpy Part-1.txt

Syntax-2: numpy.random.randint(Low,High)-----> Random number between Low to High-1 Syntax-2: numpy.random.randint(Low,High,size)----- Random number between Low to ...