Some simple machine learning algorithms, which are given as threshold rules or hypercubes, will be mentioned for helping understanding the machine learning algorithms. As a typical type of machine learning algorithm, the linear classifier is expressed as a linear equation. This chapter is intended to...
Simple machine learning algorithm for crystal lang Topics machine-learning-algorithms Resources Readme License MIT license Activity Stars 44 stars Watchers 8 watching Forks 5 forks Report repository Releases No releases published Packages No packages published Languages Crystal 100.0% Footer...
MLKit (a.k.a Machine Learning Kit) 🤖MLKit is a simple machine learning framework written in Swift. Currently MLKit features machine learning algorithms that deal with the topic of regression, but the framework will expand over time with topics such as classification, clustering, recommender ...
This article presents a general class of associative reinforcement learning algorithms for connectionist networks containing stochastic units. These algori
even conservative ones like manufacturing. In this phase, everything is connected, including cars, homes, farms, patients, and logistics. Traditional business is a thing of the past, the cost of sensors and computing power has plummeted, and smarter algorithms are in play, accelerating transformati...
A unified API standardizes many of today’s tools, frameworks, and algorithms, streamlining the distributed ML experience. This enables developers to quickly compose disparate ML frameworks for use cases that require more than one framework, such as web-supervised learning, search engine ...
Always important to remember — there is never a sole way to solve a problem in the machine learning world. There are always several algorithms that fit, and you have to choose which one fits better. Everything can be solved with a neural network, of course, but who will pay for all ...
Abstract Machine-learning models have recently encountered enormous success for predicting the properties of materials. These are often trained based on data that present various levels of accuracy, with typically much less high- than low-fidelity data. In order to extract as much information as poss...
The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features. Neuroimage 178, 622–637 (2018). Article PubMed Google Scholar He, T. et al. Deep neural networks and kernel regression achieve comparable accuracies ...
Machine learning, together with many other advanced data processing paradigms, fits incredibly well to the parallel-processing architecture that GPU computing offers. In this article you’ll learn how…