Search Results for "spreadsheet machine learning" - Page 33
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Showing 2009 open source projects for "spreadsheet machine learning"
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Sudoku Solver For Windows
A Sudoko Solver/Puzzle Generator For MS Windows
...Key Features: * Interactive puzzle input * Multiple advanced solving algorithms * Puzzle generation with guaranteed unique solutions * Save/load functionality with multiple slots * Export puzzles to an Excel compatible spreadsheet *Modern Windows interface with full mouse/keyboard support * Colored display for better visualization * Comprehensive solving step logging * Step-by-step or automatic solving modes Clean, user-friendly interface makes solving complex puzzles intuitive. Perfect for puzzle enthusiasts and anyone interested in learning advanced Sudoku solving techniques. -
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Suricata Anti-DDoS Lab
Suricata VMware VM dor IDS practicing
Suricata Anti-DDoS Security Lab (Debian 13 VMware Virtual Machine): Preconfigured VMware virtual machine for educational network security monitoring and intrusion detection using Suricata. Designed for hands-on IDS and SOC-style training in a controlled lab environment. Includes the following integrated services: + Suricata – network intrusion detection and traffic inspection + EveBox – alert visualisation and event analysis + DVWA – vulnerable web application for traffic generation and testing + phpMyAdmin – database management and inspection Default setup demonstrates DDoS-related detection scenarios, but the lab is fully customisable for other network-based attacks. ... -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is... -
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GASCAP
GASCAP can evaluate adsorption in high-throughput way
...The pseudoatom and graph Voronoi diagram method are used to figure out the unequal adsorption sites from any substrates, then the coadsorption structure can be built between substrates and any adsorbates in high-throughput way. The universal machine learning interatomic potentials are used to accelerate the adsorption energy calculations, and the postprocessing toolkits contain the functions of analyzing adsorption energy, calculating work function and charge transfer. -------------------------------- Install Method -------------------------------- set environment variable in Linux system: export PATH=/public/home/yiwc/software/GASCAP/v0.6/GASCAP-v0.6:$PATH if there is any incompatibility problem, please fix them with: .... -
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PyDenseCRF
Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs
PyDenseCRF is a Python library that provides a wrapper around the implementation of fully connected Conditional Random Fields (CRFs) developed by Philipp Krähenbühl and Vladlen Koltun. The project allows developers and researchers to integrate Dense CRF inference into Python-based machine learning pipelines, particularly for computer vision tasks such as image segmentation and labeling. Conditional Random Fields are probabilistic graphical models used to model contextual relationships between neighboring pixels or features, improving prediction consistency across images. By implementing a fully connected CRF model with Gaussian edge potentials, the library enables efficient inference across all pixel pairs in an image rather than only local neighborhoods. ... -
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PoseidonQ - AI/ML Based QSAR Modeling
ML based QSAR Modelling And Translation of Model to Deployable WebApps
- This Software was made with an intention to make QSAR/QSPR development more efficient and reproducible. - Published in ACS, Journal of Chemical Information and Modeling . Link : https://pubs.acs.org/doi/10.1021/acs.jcim.4c02372 - Simple to use and no compromise on essential features necessary to make reliable QSAR models. - From Generating Reliable ML Based QSAR Models to Developing Your Own QSAR WebApp. For any feedback or queries, contact kabeermuzammil614@gmail.com - Available on... -
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Foolbox
Python toolbox to create adversarial examples
...Foolbox is a Python library that lets you easily run adversarial attacks against machine learning models like deep neural networks. It is built on top of EagerPy and works natively with models in PyTorch, TensorFlow, and JAX. -
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TensorFlow Privacy
Library for training machine learning models with privacy for data
Library for training machine learning models with privacy for training data. This repository contains the source code for TensorFlow Privacy, a Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy. The library comes with tutorials and analysis tools for computing the privacy guarantees provided. -
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Zylthra
Zylthra: A PyQt6 app to generate synthetic datasets with DataLLM.
Welcome to Zylthra, a powerful Python-based desktop application built with PyQt6, designed to generate synthetic datasets using the DataLLM API from data.mostly.ai. This tool allows users to create custom datasets by defining columns, configuring generation parameters, and saving setups for reuse, all within a sleek, dark-themed interface. -
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snorkel
A system for quickly generating training data with weak supervision
...Snorkel Flow, an end-to-end machine learning platform for developing and deploying AI applications. Snorkel Flow incorporates many of the concepts of the Snorkel project with a range of newer techniques around weak supervision modeling, data augmentation, multi-task learning, data slicing and structuring. -
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applied-ml
Papers & tech blogs by companies sharing their work on data science
The applied-ml repository is a rich, curated collection of papers, technical articles, and case-study blog posts about how machine learning (ML) and data-driven systems are applied in real production environments by major companies. Instead of focusing solely on theoretical ML research, this repo highlights industry-scale challenges: data collection, quality, infrastructure, feature stores, model serving, monitoring, scalability, and how ML is embedded in product workflows. ... -
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Amoeba
Linux Command Line Learning Program
Amoeba is a Linux command-line learning program that observes and adapts to the Linux command line storing learned strings and their usage data. It enhances command-line proficiency by capturing command outputs, adapting string lengths, and periodically saving knowledge. Sandboxing is essential for security, and optionally a virtual machine would further isolates it from the host system. -
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...It implements the event stream processing as a library embeddable in C++ and Perl. You can think of the Complex Event Processing engine as an in-memory database driven by triggers, or a data-flow machine, or a spreadsheet on steroids (and without the GUI part).
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Fondant
Production-ready data processing made easy and shareable
Fondant is a modular, pipeline-based framework designed to simplify the preparation of large-scale datasets for training machine learning models, especially foundation models. It offers an end-to-end system for ingesting raw data, applying transformations, filtering, and formatting outputs—all while remaining scalable and traceable. Fondant is designed with reproducibility in mind and supports containerized steps using Docker, making it easy to share and reuse data processing components. ... -
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STK
a Small (Matlab/Octave) Toolbox for Kriging
...Even though it is, currently, mostly geared towards the Design and Analysis of Computer Experiments (DACE), the STK can be useful for other applications areas (such as Geostatistics, Machine Learning, Non-parametric Regression, etc.). -
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realtime-datalake
Realtime-Datalake: Real-time data ingestion, storage, and analysis.
...It enables efficient processing across multiple sources and supports scalable storage solutions. The platform can be deployed as a standalone server or in the cloud, providing flexibility and ease of setup without requiring prior data engineering or machine learning skills. With a customizable React-based UI and a Python-powered backend, it allows easy management and analysis of large data volumes. Suitable for applications like business intelligence, predictive analytics, and IoT data handling, Realtime-Datalake provides performance and scalability for real-time data processing and integration. ... -
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MediaPipe Face Detection
Detect faces in an image
The MediaPipe Face Detection model is a high-performance, real-time face detection solution that uses machine learning to identify faces in images and video streams. It is optimized for mobile and embedded platforms, offering fast and accurate face detection while maintaining a small memory footprint. This model supports multiple face detections and is highly efficient, making it suitable for a variety of applications such as augmented reality, user authentication, and facial expression analysis. -
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airda
airda(Air Data Agent
airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes. -
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...Our bot supports the following networks: Ethereum Fuse Telos Meter Moonriver Polygon PoS Avalanche Theta Fantom Harmony Shard-0 Binance Smart Chain With advanced AI algorithms and machine learning capabilities, this bot is your go-to tool for achieving consistent trading success in the fast-paced crypto market.
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CollabAI
Enhance sales and satisfaction with Collab.ai's AI-driven platform.
Empowering businesses with AI-driven customer engagement solutions. Our innovative platform combines machine learning and natural language processing to automate interactions, boost sales, and enhance customer satisfaction. Experience the future of customer engagement with Collab.ai – where every interaction drives growth and success. -
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hookprobe
Free AI that blocks hackers while you sleep. Runs on cheap hardware
HookProbe is an open-source AI-native intrusion detection system (IDS/IPS) that runs on Raspberry Pi and edge devices. It combines eBPF/XDP kernel-level packet filtering with machine learning threat classification to deliver autonomous network security with zero cloud dependency. The stack includes NAPSE (AI packet inspection), HYDRA (threat intelligence pipeline), SENTINEL (ML classification engine), and AEGIS (autonomous defense orchestrator). In production, a single Raspberry Pi 5 processes 11M+ security events, classifies 177K ML verdicts, and tracks 11,800+ attacker IPs — all autonomously. ... -
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TensorFlow Hub
A library for transfer learning by reusing parts of TensorFlow models
...These models can be loaded directly into TensorFlow pipelines and fine-tuned for new tasks using transfer learning techniques. The repository supports contributions from the community, allowing developers to submit models that become available for use by other machine learning practitioners. By enabling reusable model modules, TensorFlow Hub significantly reduces development time and computational cost when building machine learning systems. -
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ChemCrow
Chemcrow
ChemCrow is an AI-powered framework designed to assist in chemical research and discovery. It integrates AI models with chemical knowledge bases to provide intelligent recommendations for synthesis planning, reaction prediction, and material discovery. This tool helps automate and accelerate research in computational chemistry and drug development. -
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PyTextRank
Python implementation of TextRank algorithms
PyTextRank is a Python implementation of TextRank as a spaCy pipeline extension, for graph-based natural language work -- and related knowledge graph practices. -
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Kucing7 Linux Operating System
Lightweight X86/64 OS for devs/office with offline 1-click install.
Kucing7 Linux is a high-performance, Slackware-based operating system (kern. 6.18.22) designed for developers and office professionals who value speed and independence. Built with the lightweight XFCE desktop environment, it ensures a snappy experience even on older hardware while providing a modern workflow. The standout feature of Kucing7 is its "Offline-First" philosophy. Unlike many modern distros that require a constant internet connection to fetch dependencies, Kucing7 allows you to...
