Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Abstract: Distributed gradient descent has attracted attention in modern machine learning, especially for handling large datasets. Less focus has been given to the distributed gradient descent where ...

Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning. Supreme Court, with no dissents, rejects GOP challenge to California's new election ...

Brenna Henn had a long-term grant to study the genetic diversity of Africans and people of African descent. Then her N.I.H. funding was cut. Credit...Andri Tambunan for The New York Times Supported by ...

PythoC lets you use Python as a C code generator, but with more features and flexibility than Cython provides. Here’s a first look at the new C code generator for Python. Python and C share more than ...

In this tutorial, we explore how we can seamlessly run MATLAB-style code inside Python by connecting Octave with the oct2py library. We set up the environment on Google Colab, exchange data between ...

The first chapter of Neural Networks, Tricks of the Trade strongly advocates the stochastic back-propagation method to train neural networks. This is in fact an instance of a more general technique ...

In this tutorial, we demonstrate how to efficiently fine-tune the Llama-2 7B Chat model for Python code generation using advanced techniques such as QLoRA, gradient checkpointing, and supervised ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Abstract: Based on Stochastic Gradient Descent (SGD), the paper introduces two optimizers, named Interpolational Accelerating Gradient Descent (IAGD) as well as Noise-Regularized Stochastic Gradient ...