“Python for scientific computing” an on-line course on TwitchTV aimed to improve your scientific Python skills starting Tuesday 25th November at 10:00 (3 days, 4 hours per day). The course is ...

In 2005, Travis Oliphant was an information scientist working on medical and biological imaging at Brigham Young University in Provo, Utah, when he began work on NumPy, a library that has become a ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...

One of the long-standing bottlenecks for researchers and data scientists is the inherent limitation of the tools they use for numerical computation. NumPy, the go-to library for numerical operations ...

Abstract: It has recently been shown that a typical implementation of Simulated Annealing in continuous domains is effectively the same as random search/Hill Climbing. This result is repeated for Dual ...

Abstract: Artificial intelligence (AI) is gradually transforming the landscape of medical practice. Advances in digitized data gathering, machine learning, and computational resources have made it ...

Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in Python ...

Thank you for your interest in applying for Google Summer of Code with CuPy! CuPy is a NumPy/SciPy-compatible array library for GPU-accelerated computing with Python. CuPy acts as a drop-in ...