Scientific Research Publishing

Bikku, T. (2020) Multi-Layered Deep Learning Perceptron Approach for Health Risk Prediction. Journal of Big Data, 7, Article No. 50.

ABSTRACT: Lung cancer stands as the preeminent cause of cancer-related mortality globally. Prompt and precise diagnosis, coupled with effective treatment, is imperative to reduce the fatality rates ...
Scientific Research Publishing

Nosratabadi, S., Ardabili, S., Lakner, Z., Mako, C. and Mosavi, A. (2021) Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS ...

ABSTRACT: Egg loss is one of the major problems in the egg hatching industry. This study aims to support farmers in optimizing their egg hatch through the development of a prediction model. This is to ...
Hosted on MSN

Supervised Learning Example | Easy Explanation with Real-Life Use Case

What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.
IEEE

One-bit SAR Imaging Based on Perceptron Learning Algorithm with Bootstrap Method

Abstract: The one-bit quantization with time-varying thresholds has been studied in the field of compressed sensing and SAR imaging. The Perceptron Learning Algorithm (PLA) uses a sign function as its ...
GitHub

Here I'm gonna implement a perceptron from scratch and with out any frameworks ...

Implementing a simple percepron and training it with gradient descent optimizer for linear regression task with out any frameworks such as Keras etc. The first one is 1.py which is a simple ...
IEEE

Convergence models for Rosenblatt's perceptron learning algorithm

Abstract: Presents a stochastic analysis of the steady-state and transient convergence properties of a single-layer perceptron for fast learning (large step-size, input-power product). The training ...