Topic: classifier Goto Github
Some thing interesting about classifier
Some thing interesting about classifier
classifier,Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
User: aangelopoulos
classifier,HN To E-book
User: abishekmuthian
classifier,A Machine Learning classifier for recognizing the digits for humans 🎰
User: akshaybahadur21
classifier,Object classification with CIFAR-10 using transfer learning
User: alexisbcook
classifier,Machine learning based text classification in JavaScript using n-grams and cosine similarity
User: andreekeberg
Home Page: https://www.npmjs.com/package/ml-classify-text
classifier,Image Segmentation using Texture and Color features in C++
User: ankitdhall
classifier,An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more
Organization: axa-group
classifier,A collection of research papers on decision, classification and regression trees with implementations.
User: benedekrozemberczki
classifier,A curated list of data mining papers about fraud detection.
User: benedekrozemberczki
classifier,A curated list of gradient boosting research papers with implementations.
User: benedekrozemberczki
classifier,The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
User: benedekrozemberczki
classifier,licensechecker (lc) a command line application which scans directories and identifies what software license things are under producing reports as either SPDX, CSV, JSON, XLSX or CLI Tabular output. Dual-licensed under MIT or the UNLICENSE.
User: boyter
classifier,ERRor ANnotation Toolkit: Automatically extract and classify grammatical errors in parallel original and corrected sentences.
User: chrisjbryant
classifier,A Naive Bayesian Classifier written in Python
User: codebox
Home Page: https://codebox.net/pages/naive-bayesian-classifier-in-python
classifier,Efficient tree-based convolutional neural networks in TensorFlow
User: crestonbunch
classifier,Organize your folders into a beautiful classified folder structure with this perfect tool
User: d6o
Home Page: https://disiqueira.github.io/Gorganizer/
classifier,Machine Learning inference engine for Microcontrollers and Embedded devices
Organization: emlearn
classifier,An example of how to use CreateML in Xcode 10 to create a Core ML model for classifying text
Organization: flight-school
Home Page: https://flight.school/articles/classifying-programming-languages-with-createml/
classifier,A DHT crawler and torrent indexer
User: flyersweb
classifier,A Naive Bayes machine learning implementation in Elixir.
User: fredwu
classifier,Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].
User: gionanide
classifier,Facial Emotion Recognition on FER2013 Dataset Using a Convolutional Neural Network
User: gitshanks
classifier,A License Classifier
Organization: google
classifier,Building classifiers using cancer transcriptomes across 33 different cancer-types
Organization: greenelab
classifier,Natural language detection library for Rust. Try demo online: https://whatlang.org/
User: greyblake
Home Page: https://whatlang.org/
classifier,Machine learning algorithms in Dart programming language
User: gyrdym
Home Page: https://gyrdym.github.io/ml_algo/
classifier,Scene text detection and recognition based on Extremal Region(ER)
User: hsiehyichia
classifier,A simple web app that shows how Watson's Natural Language Classifier (NLC) can classify ICD-10 code. The app is written in Python using the Flask framework and leverages the Watson Developer Cloud Python SDK
Organization: ibm
Home Page: https://developer.ibm.com/patterns/classify-icd-10-data-with-watson/
classifier,Chatto is a minimal chatbot framework in Go.
User: jaimeteb
Home Page: https://chatto.jaimeteb.com
classifier,Audio feature extraction and classification
User: jsingh811
classifier,ALBERT model Pretraining and Fine Tuning using TF2.0
User: kamalkraj
classifier,This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en
User: karolzak
classifier,A sophisticated smart symptom search engine
User: leanderme
Home Page: http://sytora.com
classifier,Simple hand classifier by Pytorch and ResNet
User: limeng95
classifier,This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
Organization: microsoft
classifier,alibaba MNN, mobilenet classifier, centerface detecter, ultraface detecter, pfld landmarker and zqlandmarker, mobilefacenet
User: mirroryuchen
classifier,ncnn example: mask detection: anticonv face detection: retinaface&&mtcnn&¢erface, track: iou tracking, landmark: zqcnn, recognize: mobilefacenet classifier: mobilenet object detecter: mobilenetssd
User: mirroryuchen
classifier,yet another general purpose naive bayesian classifier.
User: muatik
classifier,A .NET image and video classifier used to identify explicit/pornographic content written in C#.
Organization: nsfwspy
classifier,A pytorch implemented classifier for Multiple-Label classification
User: pangwong
classifier,A java classifier based on the naive Bayes approach complete with Maven support and a runnable example.
User: ptnplanet
classifier,The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch
User: pythonlessons
Home Page: https://pylessons.com/
classifier,Search the best feature subset for you classification mode
User: renatoosousa
classifier,Implementation of Convolutional enhanced image Transformer
User: rishikksh20
classifier,Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
User: rishikksh20
classifier,Real-Time Spatio-Temporally Localized Activity Detection by Tracking Body Keypoints
User: smellslikeml
Home Page: https://www.hackster.io/actionai/actionai-custom-tracking-multiperson-activity-recognition-fa5cb5
classifier,This is a pytorch re-implementation of Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition
User: songdejia
classifier,Machine learning to classify Malicious (Spam)/Benign URL's
User: surajr
classifier,NaiveBayes classifier for JavaScript
User: surmon-china
Home Page: https://github.surmon.me/naivebayes
classifier,Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive Language", ICWSM 2017
User: t-davidson
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
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JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
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We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.