Search Results for "classification" - Page 8
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Showing 773 open source projects for "classification"
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Transformers in Time Series
A professionally curated list of awesome resources
...The project was created to systematically organize the rapidly growing research field that applies transformer architectures to time series modeling tasks. It compiles literature from major conferences and journals and categorizes them by application domains such as forecasting, anomaly detection, and classification. The repository also provides a taxonomy that helps researchers understand different architectural variations of transformers designed for time series data. These models are particularly important because transformers can capture long-range dependencies in sequential data, which makes them well suited for complex temporal patterns in real-world datasets. -
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Mister knock Compta
Accounting on Office365 / Comptabilité sous Office 365
The page is about mkCompta, a software running on Office 365 that allows users to manage their accounting by importing banking transactions from their bank.Uses an Access database for data handling.Utilizes an Excel file for data consultation.Imports banking transactions from CSV files.Groups expenses and income by budget and associates funds with a financial asset (bank account, life insurance, portfolio, etc.). / La page concerne mkCompta, un logiciel fonctionnant sous Office 365... -
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onlyjobs-desktop
Private AI job tracker with gmail sync that runs on your local machine
...Using a powerful 3B parameter AI model that runs entirely on your Mac, it intelligently classifies emails into job applications, interviews, offers, and rejections without sending data to any servers. Key features include one-click Gmail sync supporting multiple accounts, smart deduplication that merges related job emails, and instant classification of company names, positions, and application status. View original emails with a single click to verify classifications. Built with Electron and React for a smooth native experience, OnlyJobs Desktop prioritizes privacy - all AI processing happens locally on your device. The 4GB download includes the complete Llama 3.2 model, enabling fully offline operation after initial Gmail sync. ... -
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OptiMIClass
Automatic n-dimensional data clustering tool powered by five advanced
...Juan José Fallas-Monge at the Instituto Tecnológico de Costa Rica (TEC), School of Mathematics, with support from the Vice-Rectory for Research and Extension (VIE). The software was a direct outcome of “Combinatorial optimization heuristics for data classification” (Code: 5402-1440-3901), and its development continued within the related project “Disease propagation: heuristics applied to optimizing control measures” (Code: 540114404201). -
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DocWire SDK
Award-winning modern data processing SDK in C++20
DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to... -
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MBR WP Performance
Comprehensive WordPress performance optimization plugin
MBR WP Performance is the WordPress optimisation plugin for users who want real control. Instead of hiding complexity behind a single button, it provides transparent, granular controls for every performance technique—so you understand exactly what each feature does. Core Features: Disable WordPress features that you don’t need. Self-host and preload Google Fonts, lazy load images and videos, defer/delay JavaScript execution, generate and inline critical CSS, preload critical resources,... -
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Book-Reviews-In-Mathematica
Partial Differential Equations, Complex Analysis, Mathematica, Farlow
Cliff* Notes, Mathematica Evaluatable "Partial Differential Equations for Scientists and Engineers", Farlow "Physics for Scientists and Engineers", Serway "A First Course in Complex Analysis", Beck "PDE", Asmar "PDE, An Introduction", Colton "Elementary Differential Equations", 7th, Rainville "Ordinary Differential Equations", Tenenbaum "Linear Algebra And It's Applications", Lay "Swokowski Calculus", 5th, Swokowski "Chemistry Concepts & Problems, A Self-Teaching Guide",... -
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scikit-learn-videos
Jupyter notebooks from the scikit-learn video series
...It provides the Jupyter notebooks used in each lesson so learners can reproduce the demonstrations and experiment with the code themselves. The series introduces fundamental machine learning concepts such as classification, regression, model evaluation, feature engineering, and cross-validation using clear examples and real datasets. Each video corresponds to a notebook that walks through the code step by step, allowing students to see both the theoretical explanation and its practical implementation. The project emphasizes accessibility and beginner-friendly explanations, making it suitable for learners who are new to data science or machine learning programming. ... -
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Weak-to-Strong
Implements weak-to-strong learning for training stronger ML models
...The project provides tools for training larger “strong” models using labels or guidance generated by smaller “weak” models. Its core functionality focuses on binary classification tasks, with support for fine-tuning pretrained language models and experimenting with different loss functions, including confidence-based auxiliary losses. The repository also includes a dedicated vision module for applying weak-to-strong training setups in computer vision, demonstrated with models such as AlexNet and DINO on ImageNet. ... -
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Deep Learning Models
A collection of various deep learning architectures, models, and tips
...The code favors readability and pedagogy: components are organized so you can trace data flow through layers, losses, optimizers, and evaluation. Examples span fundamental architectures—MLPs, CNNs, RNN/Transformers—and practical tasks like image classification or text modeling. Reproducible training scripts and configuration files make it straightforward to rerun experiments or adapt them to your own datasets. The repo often pairs implementations with notes on design choices and trade-offs, turning it into both a toolbox and a learning resource. It’s suitable for students, researchers prototyping ideas, and practitioners who want clean baselines before adding complexity. -
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TensorFlow Hub
A library for transfer learning by reusing parts of TensorFlow models
TensorFlow Hub is a repository that provides a library and platform for publishing, discovering, and reusing pre-trained machine learning models built with TensorFlow. The project enables developers to integrate high-quality models into their applications without needing to train them from scratch. Through TensorFlow Hub, researchers and practitioners can share reusable model components such as image classifiers, text embedding models, and object detection networks. These models can be... -
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YAYI
Repo for YaYi Chinese LLMs based on LlaMA2 & BLOOM
...The architecture is based on transformer-style language models optimized for conversational understanding and generation. In addition to producing coherent responses, the system is designed to handle tasks such as summarization, translation, question answering, and text classification. The repository provides model checkpoints, training resources, and inference tools that allow developers to deploy the model in their own applications. By releasing both the model and supporting infrastructure, the project encourages experimentation and research in multilingual AI systems. -
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pattern_classification
A collection of tutorials and examples for solving machine learning
...It includes notebooks and guides that demonstrate data preprocessing, feature extraction, model training, and evaluation techniques used in machine learning workflows. The repository also covers algorithms such as Bayesian classification, logistic regression, neural networks, clustering methods, and ensemble models. In addition to algorithm tutorials, the project contains supplementary resources such as dataset collections, visualization examples, and links to recommended books and talks. These materials are designed to support both theoretical understanding and practical experimentation with machine learning tools. -
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GPT-2 Output Dataset
Dataset of GPT-2 outputs for research in detection, biases, and more
...The repository provides scripts and metadata for working with the dataset, with the goal of supporting research in areas like detection, evaluation of text coherence, and analysis of generative models. While no active development is expected, the dataset remains a useful benchmark for tasks involving text classification, style analysis, and generative model evaluation. -
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Alink
Alink is the Machine Learning algorithm platform based on Flink
Alink is Alibaba’s scalable machine learning algorithm platform built on Apache Flink, designed for batch and stream data processing. It provides a wide variety of ready-to-use ML algorithms for tasks like classification, regression, clustering, recommendation, and more. Written in Java and Scala, Alink is suitable for enterprise-grade big data applications where performance and scalability are crucial. It supports model training, evaluation, and deployment in real-time environments and integrates seamlessly into Alibaba’s cloud ecosystem. -
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Faum
Fast Autonomous Unsupervised Multidimiensional Classification
This is the proof-of-concept implementation of the FAUM Clustering method. This implementation was used to perform the published results and is now released in the hope that it will be useful. -
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Artifact GeoMorph Toolbox 3D 3.1
A toolbox for 3DGM shape analysis of archaeological artifacts
The Artifact Geomorph Toolbox 3D software is designed to provide the archaeologist interested in artifact shape variability with a toolbox to allow the acquisition, analysis and results exploration of homologous 3D landmark-based geometric morphometric data. As such, the toolbox contains an automated item and semi-landmarks positioning procedure and the fundamental statistical analyses and procedures to allow the processing and analysis of the data. It is designed to be easy to use and... -
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Autolabel
Label, clean and enrich text datasets with LLMs
Autolabel is a Python library to label, clean and enrich datasets with Large Language Models (LLMs). Autolabel data for NLP tasks such as classification, question-answering and named entity recognition, entity matching and more. Seamlessly use commercial and open-source LLMs from providers such as OpenAI, Anthropic, HuggingFace, Google and more. -
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Detic
Code release for "Detecting Twenty-thousand Classes
Detic (“Detecting Twenty-thousand Classes using Image-level Supervision”) is a large-vocabulary object detector that scales beyond fully annotated datasets by leveraging image-level labels. It decouples localization from classification, training a strong box localizer on standard detection data while learning classifiers from weak supervision and large image-tag corpora. A shared region proposal backbone feeds a flexible classification head that can expand to tens of thousands of categories without exhaustive box annotations. The system supports zero- or few-shot extension to novel categories via semantic embeddings and class name supervision, making “open-world” detection practical. ... -
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Doctor Dignity
Doctor Dignity is an LLM that can pass the US Medical Licensing Exam
...It also highlights privacy-aware patterns and cautions that this kind of software must not replace licensed medical advice. As a teaching and ideation vehicle, the project invites contributors to iterate on intent classification, response templates, and safe-use boundaries. -
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funNLP
Resources, corpora, and tools for Chinese natural language processing
...It aggregates datasets, lexicons, wordlists, sentiment dictionaries, knowledge graphs, and pretrained model references, serving as a one-stop resource hub for Chinese NLP practitioners. The repository is organized into categories such as sentiment analysis, text classification, named entity recognition, knowledge graphs, and various lexicons (e.g. sensitive words, emotion dictionaries, stopwords). It also includes links to academic papers, open-source model implementations, and practical utilities like word segmentation or text cleaning scripts. The project is highly community-oriented, frequently updated with contributions and new resources, and it’s widely used in both academic and applied NLP research. ... -
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Ultimate AppLocker Bypass List
The most common techniques to bypass AppLocker
UltimateAppLockerByPassList is a community-curated repository that collects known techniques, patterns, and candidate binaries that have been observed or proposed to bypass Microsoft AppLocker and similar executable control policies. The project functions as a living catalog: entries list binaries, script hosts, and patterns that researchers have tested or reported in the wild, along with notes about context, platform constraints, and mitigation ideas. It is aimed primarily at defenders,... -
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Lingua-Go
The most accurate natural language detection library for Go
...Its task is simple: It tells you which language some text is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine-learning frameworks or natural language processing applications. In cases where you don't need the full-fledged functionality of those systems or don't want to learn the ropes of those, a small flexible library comes in handy. -
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...Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007 Aug;73(16):5261-7. 2. Wang Q, Cole JR. Updated RDP taxonomy and RDP Classifier for more accurate taxonomic classification. Microbiol Resour Announc. 2024 Apr 11;13(4):e0106323.
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MMClassification
OpenMMLab Image Classification Toolbox and Benchmark
MMClassification is an open-source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. Supports DenseNet, VAN and PoolFormer, and provide pre-trained models. Supports training on IPU. Supports a series of CSP networks, such as CSP-ResNet, CSP-ResNeXt and CSP-DarkNet. MMClassification is an open source project that is contributed by researchers and engineers from various colleges and companies.
