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Showing 15 open source projects for "predict number"
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Circuitscape.jl
Algorithms from circuit theory to predict connectivity
Circuitscape is an open-source program that uses circuit theory to model connectivity in heterogeneous landscapes. Its most common applications include modeling the movement and gene flow of plants and animals, as well as identifying areas important for connectivity conservation. The new Circuitscape is built entirely in the Julia language, a new programming language for technical computing. Julia is built from the ground up to be fast. As such, this offers a number of advantages over... -
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spacy-transformers
Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spaCy supports a number of transfer and multi-task learning workflows that can often help improve your pipeline’s efficiency or accuracy. Transfer learning refers to techniques such as word vector tables and language model pretraining. These techniques can be used to import knowledge from raw text into your pipeline, so that your models are able to generalize better from your annotated examples. You can convert word vectors from popular tools like FastText and Gensim, or you can load in any pre... -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
... network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models. In total, 17 benchmark datasets are used for comparison, which can be downloaded at ODDS. -
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Iperf 2
A means to measure network responsiveness and throughput
Iperf here is a means of measuring networks - capacity & latency (including ECN) over sockets both TCP and UDP. The goals include maintaining an active iperf code base across a broad set of platforms and operating systems. This is a multi-threaded design that scales with the number of CPUs or cores within a system. It supports both high impact and low impact techniques to obtain and report network performance. Current release: 2.2.0, April 10, 2024 (2.2.1 per coming soon) About iperf 2... -
Powerful small business accounting softwareWith AccountEdge, business owners can organize, process, and report on their financial information so they can focus on their business. Features include: accounting, integrated payroll, sales and purchases, contact management, inventory tracking, time billing, and more.
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ModelFox
ModelFox makes it easy to train, deploy, and monitor ML models
... learning model by running modelfox train with the path to a CSV file and the name of the column you want to predict. The CLI automatically transforms your data into features, trains a number of linear and gradient boosted decision tree models to predict the target column, and writes the best model to a .modelfox file. If you want more control, you can provide a config file. -
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Stake-predictor
The Stake Crash Predictor is a tool designed to predict the next multi
The Stake Crash Predictor is a tool designed to predict the next multiplier number in crash game on stake. It utilizes advanced machine learning techniques to provide predictions for crash game depending on the api data. Features Data Analysis: The predictor leverages historical market data to identify patterns and trends that may indicate an upcoming crash. Machine Learning Models: Advanced ML models are employed to learn from the historical data and make accurate crash predictions... -
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RQ-Transformer
Implementation of RQ Transformer, autoregressive image generation
Implementation of RQ Transformer, which proposes a more efficient way of training multi-dimensional sequences autoregressively. This repository will only contain the transformer for now. You can use this vector quantization library for the residual VQ. This type of axial autoregressive transformer should be compatible with memcodes, proposed in NWT. It would likely also work well with multi-headed VQ. I also think there is something deeper going on, and have generalized this to any number... -
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node-markov-generator
Generates simple sentences based on given text corpus
This simple generator emits short sentences based on the given text corpus using a Markov chain. To put it simply, it works kinda like word suggestions that you have while typing messages in your smartphone. It analyzes which word is followed by which in the given corpus and how often. And then, for any given word it tries to predict what the next one might be. Here you create an instance of TextGenerator passing an array of strings to it - it represents your text corpus which will be used... -
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DETR
End-to-end object detection with transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based... -
Business Texting and Text Message Marketing Solutions - TextellentTextellent's business texting solution makes designing, managing, measuring, and integrating SMS and MMS campaigns easy. Whether used for customer service, sales, or marketing, Textellent supports your customer journey with an easy-to-use service that text-enables local business lines and serves businesses of any size. Robust scheduling and appointment reminders are also available, as are keywords and shortcodes for easy opt-in programs with TCPA compliance supported by AI.
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JCVI VIGOR
Viral Genome ORF Reader
VIGOR (Viral Genome ORF Reader) is a perl application to predict protein sequences encoded in viral genomes. VIGOR determines the protein coding sequences by sequence similarity searching against curated viral protein databases. Please see the wiki to see list of all supported viruses. This work has been funded in whole or part with federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services under... -
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mCarts
A hidden Markov model to predict clustered RNA motif sites
Many RBPs recognize very short and degenerate sequences, with targeting specificity achieved by mechanisms such as synergistic binding to multiple clustered sites and modulation of site accessibility through different RNA-secondary structures. mCarts integrates the number and spacing of individual motif sites, their accessibility and conservation, which substantially improves signal to noise ratio. This algorithm learns and quantifies rules of these features, taking advantage of a large number... -
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CloisterWalk
Reveal fractal patterns in irrational numbers
CloisterWalk can test your favorite number or will let you choose a number from a list. Many provided numbers are known irrationals, others are still uncertain. Enter the number of steps you would like to walk and click the Go button to produce a graph. If a number does not seem interesting, try switching between the square and hexagonal grids. Can you predict what is going to happen next time you click the Go button? Can you figure out why fractal patterns emerge? Can CloisterWalk... -
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PseudoDomain
Accurate identification of pseudogenes without genome annotations
Pseudogenes are dysfunctional DNA sequences that share sequence similarities with functional genes. Accurate identification of pseudogenes is important to understand biological and evolutionary histories of genomes and genes. PseudoDomain is a processed pseudogene identification tool with high sensitivity and low false positive rate. It can identify pseudogenes in species that do not have accurate genome annotations. In addition, it can accurately predict the number and positions of frameshifts... -
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CRUMp
A probabilistic prediction system of protein phosphorylation sites
... the accession number of the protein sequence and the position numbers of known phosphorylation sites. Note that CRUMp may predict additional phosphorylation sites that have not been experimentally verified yet. The testing dataset is from Biswas et al. 2010, http://www.biomedcentral.com/1471-2105/11/273/additional. -
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vCGH (virtual CGH) is a program that use microarray gene expression data to predict DNA copy number abberation in lymphoma samples.
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