TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
Hacker

A Quick Introduction to Python Numpy for Beginners

I like Anime, Chess, Deep Learning, Mathematics and Programming. NumPy is a Python library that is mainly used to work with arrays. An array is a collection of items that are stored next to each other ...
marktechpost

NVIDIA AI Releases cuPyNumeric: A Drop-in Replacement Library for NumPy Bringing Distributed and Accelerated Computing for Python

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 ...
TheServerSide

Speed up Python and NumPy by avoiding the conversion tax

There is a phenomenon in the Python programming language that affects the efficiency of data representation and memory. I call it the "invisible line." This invisible line might seem innocuous at ...
InfoWorld

Use Cython to accelerate array iteration in NumPy

NumPy is known for being fast, but could it go even faster? Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with data in ...
techentice.com

NumPy: Difference between reshape(), flatten(), ravel()

NumPy or Numeric Python is a powerful library for scientific calculations. It works with ndarray (array object in NumPy) that could be single or multi- dimensional. To perform different calculations ...
syncedreview

After 15 Long Years, a NumPy Paper Finally Appears!

Since NumPy was introduced to the world 15 years ago, the primary array programming library has grown into the fundamental package for scientific computing with Python. NumPy serves as an efficient ...