From-scratch NumPy implementations of Perceptron and Multi-Layer Perceptron (MLP) for deep learning coursework, with experiments on Gaussian datasets, make_moons, and batch size analysis for BGD/SGD.

You are reading an exclusive WrapPRO article for free. Want to level up your entertainment career? Subscribe to WrapPRO. One of the issues at the heart of the WGA strike continues to be mini-rooms and ...

Abstract: Aitken gradient descent (AGD) algorithm takes some advantages over the standard gradient descent and Newton methods: 1) can achieve at least quadratic convergence in general; 2) does not ...

Several disease-modifying therapies have been developed for the treatment of the focal inflammatory manifestations of relapsing-remitting multiple sclerosis (RRMS) (clinical relapses and lesion ...

Fruit detection and counting are essential tasks for horticulture research. With computer vision technology development, fruit detection techniques based on deep learning have been widely used in ...

A fortnight ago, in the dying days of the Trump administration, the Office of the United States Trade Representative wrote a letter to Labor senator Alex Gallacher — who was chairing the forthcoming ...

A set of mini apps has gone live on Snapchat platform, marking the beginning of a new chapter for the Los Angeles-headquartered firm as it aims to emulate aspects of the popular Chinese “super-app” ...

Hi guys, I’d like to give an intro into the different types of gradient descent used. Gradient descent (GD) is an iterative algorithm to find the minima of a cost function. If this cost function is ...

This was just a fun experiment to use Gradient Descent to perform linear regression. Linear regression is all about finding the line of best fit of all given data points. This is the plot of the 'Line ...

Abstract: Low-complexity and high-performance low-density parity-check (LDPC) decoders are highly demanded in various modern communication and storage systems. In this paper, a novel hard-decision ...