安诺探测器
AnnoProbe (2022-11-12, R, 0KB, 下载0次)
transformer
transformer (2023-11-10, R, 0KB, 下载0次)
自动传送器，，
automlr,, (2018-01-28, R, 0KB, 下载0次)
使用GBIF发生数据和图形用户界面进行物种分布建模的R包，
An R package for species distribution modeling with GBIF occurrence data and a graphical user interface, (2023-08-28, R, 0KB, 下载0次)
SVM和KNN分类器，
SVM & KNN classifiers, (2023-08-23, R, 0KB, 下载0次)
刘易斯和克拉克学院的保护数据科学课程-创建物种发生图，当前气候下的物种分布模型...，
Conservation Data Science course at Lewis & Clark College- creating species occurence map, species distribution model under current climate conditions, and future distribution model in 2050 for a host milkweed plant for monarch butterflies. (2022-06-30, R, 0KB, 下载0次)
贝叶斯监听器，
Bayesian Listener, (2020-12-04, R, 0KB, 下载0次)
脑码选择器，，
braincodeselector,, (2023-03-01, R, 0KB, 下载0次)
脑瘤分类器，，
brainTumorclassifier,, (2022-01-17, R, 0KB, 下载0次)
与手稿“大脑共表达的架构揭示了疾病发生的全脑基础”相对应的代码和示例数据...，
Code and example data corresponding to the manuscript "The architecture of brain co-expression reveals the brain-wide basis of disease susceptibility" (2020-04-30, R, 0KB, 下载0次)
hips-衍生传感器神经元，，
hipscderivedsensoryneuron,, (2021-12-09, R, 0KB, 下载0次)
在R中实现2D感知器。说明感知器如何基本工作，以及在没有偏置神经元的情况下会发生什么。，
Implementation of a 2D Perceptron in R. Illustrates how a perceptron works fundamentally, and what could happen without a bias neuron., (2013-09-16, R, 0KB, 下载0次)
传感器，，
senet,, (2022-03-20, R, 603KB, 下载0次)
用于管理树分布的发生和预测数据的存储库
Repository for curating occurrence and predictor data of tree distributions (2018-06-01, R, 207KB, 下载0次)
fn dbscan集群器，，
fn-dbscan-clusterer,, (2021-06-07, R, 16KB, 下载0次)
找到经常发生紧急情况的地区，为紧急部署做好准备，甚至预防紧急情况的发生。
Find areas where emergencies occurred frequently to get ready for emergency deployment or even prevent them. (2018-05-28, R, 524KB, 下载0次)
foodborne_diseases_outbreak_prediction，一个用R语言预测因食用某些食物而可能发生的疾病的项目。数据预处理、虚拟化...
A project in R language to predict diseases that can happen from eating certain food. Data pre-processing, virtualization and deep learning algorithms are applied to analyse the data. (2019-09-17, R, 7517KB, 下载0次)
IUCNN，基于地理物种发生、环境数据和现有IUCN红色名录评估的训练神经网络...
Train neural networks based on geographic species occurrences, environmental data and existing IUCN Red List assessments to predict the conservation status of "Not Evaluated" species, for any taxon or geographic region of interest. <https://iucnn.github.io/IUCNN/> (2023-02-17, R, 1822KB, 下载0次)
Shiny的机器学习浏览器，，
Machine-Learning-Explorer-in-Shiny,, (2016-02-25, R, 4338KB, 下载0次)
无服务器ml、无服务器ml实验
serverless-ml,Serverless ML experiments (2020-01-23, R, 4KB, 下载0次)