Search Results for "visualize"
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Showing 106 open source projects for "visualize"
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Weights and Biases
Tool for visualizing and tracking your machine learning experiments
Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Quickly identify model regressions. Use W&B to visualize results in real time, all in a central dashboard. Focus on the interesting ML. Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. -
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folium
Python data, Leaflet.js maps
folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the leaflet.js library. Manipulate your data in Python, then visualize it in on a Leaflet map via folium. folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing rich vector/raster/HTML visualizations as markers on the map. The library has a number of built-in tilesets from OpenStreetMap, Mapbox, and Stamen, and supports custom tilesets with Mapbox or Cloudmade API keys. folium supports both Image, Video, GeoJSON and TopoJSON overlays. ... -
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Book4_Power-of-Matrix
Book_4_Matrix Power | The Iris Book: From Addition, Subtraction
...The material emphasizes geometric interpretation and visual reasoning, which makes abstract linear algebra topics more accessible to beginners and self-learners. The repository is continuously updated and intended to accompany the broader Visualize-ML learning ecosystem. Overall, it serves as a visually driven mathematical foundation for students preparing for data science and machine learning work. -
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
...Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative) are an amazing technology that will power many of future ML use cases. A large set of these technologies are being deployed into businesses (the real world) in what we consider a production setting. -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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URH (Universal Radio Hacker)
Universal Radio Hacker: Investigate Wireless Protocols Like A Boss
Universal Radio Hacker (URH) is a tool for investigating unknown wireless communication protocols. It supports signal capturing, decoding, modulation analysis, and protocol reverse engineering through an intuitive graphical interface. URH is used in research, security testing, and hobbyist electronics for understanding proprietary RF systems, IoT device communication, and embedded protocols. -
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LangCheck
Simple, Pythonic building blocks to evaluate LLM applications
Simple, Pythonic building blocks to evaluate LLM applications. -
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Book5_Essentials-Probability-Statistics
The book 5 of statistics in simplicity
Book5_Essentials-of-Probability-and-Statistics is a Visualize-ML educational volume that introduces the statistical and probabilistic concepts underpinning modern data analysis and machine learning. The repository explains topics such as distributions, sampling, inference, and uncertainty using visual demonstrations and intuitive narratives. Its teaching philosophy prioritizes conceptual clarity over heavy formalism, making statistical thinking more approachable for beginners. ... -
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BertViz
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
BertViz is an interactive tool for visualizing attention in Transformer language models such as BERT, GPT2, or T5. It can be run inside a Jupyter or Colab notebook through a simple Python API that supports most Huggingface models. BertViz extends the Tensor2Tensor visualization tool by Llion Jones, providing multiple views that each offer a unique lens into the attention mechanism. The head view visualizes attention for one or more attention heads in the same layer. It is based on the... -
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Book1_Python-For-Beginners
The Iris Book: Addition, Subtraction, Multiplication, and Division
Book1_Python-For-Beginners is the introductory volume of the Visualize-ML series, designed to teach Python programming to newcomers with no prior coding experience. The repository emphasizes clarity and gradual skill building, starting from fundamental syntax and moving toward practical programming patterns. It integrates visual aids and annotated code examples to help learners understand not just how Python works but why certain patterns are used. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Book3_Elements-of-Mathematics
From Addition, Subtraction, Multiplication, and Division to ML
Book3_Elements-of-Mathematics is an open learning resource in the Visualize-ML collection that introduces core mathematical foundations required for modern data science and AI. The repository presents topics such as algebra, calculus fundamentals, and mathematical reasoning using a highly visual and beginner-friendly approach. Its goal is to reduce the intimidation barrier often associated with formal mathematics by combining diagrams, structured explanations, and applied examples. ... -
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DeepBI
LLM based data scientist, AI native data application
DeepBI is an AI-native data analysis platform. DeepBI leverages the power of large language models to explore, query, visualize, and share data from any data source. Users can use DeepBI to gain data insight and make data-driven decisions. -
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Vedo
A python module for scientific analysis of 3D data
...Import meshes from VTK format, STL, Wavefront OBJ, 3DS, Dolfin-XML, Neutral, GMSH, OFF, PCD (PointCloud). Export meshes as ASCII or binary to VTK, STL, OBJ, PLY formats. Analysis tools like Moving Least Squares, mesh morphing and more. Tools to visualize and edit meshes (cutting a mesh with another mesh, slicing, normalizing, moving vertex positions, etc..). Split mesh based on surface connectivity. Extract the largest connected area. Calculate areas, volumes, center of mass, average sizes etc. Calculate vertex and face normals, curvatures, feature edges. Fill mesh holes. -
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leafmap
A Python package for interactive mapping and geospatial analysis
...However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users. It is a free and open-source Python package that enables users to analyze and visualize geospatial data with minimal coding in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. Leafmap is built upon several open-source packages, such as folium and ipyleaflet (for creating interactive maps), WhiteboxTools and whiteboxgui (for analyzing geospatial data), and ipywidgets (for designing interactive graphical user interface [GUI]). -
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Shows how a target value (e.g. "Survived" in the Titanic... -
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TimeTracker
Open-source and free to self-host
TimeTracker by DRYTRIX is a comprehensive self-hosted time tracking and project management application that helps individuals, teams, and small businesses take control of their productivity and billing. Built on a modern web stack (Python/Flask backend with a responsive frontend), TimeTracker enables users to track hours, manage projects and clients, visualize data with interactive charts, and even generate professional invoices directly from tracked time. It embraces privacy and flexibility by running entirely on your own servers, ensuring sensitive business data stays under your control, and supports real-time timer persistence via WebSockets so timers continue even if the browser is closed. ... -
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CUDOS Framework
Command Line Interface tool for Cloud Intelligence Dashboards
The AWS Cloud Intelligence Dashboards Framework is a set of open-source tools and templates designed to help organizations deploy and manage advanced data visualization dashboards that offer insights into cost, usage, governance, and operational health across AWS environments. It is part of the AWS Solutions Library and includes CloudFormation templates, CLI commands, and pre-built dashboards that collect, process, and visualize data from AWS billing, cost management, budgets, and usage reports in services such as Amazon QuickSight or other BI tools. These dashboards give finance and engineering teams the power to track spending trends, budget forecasts, account utilization patterns, and compliance signals in a unified view, enabling better governance and financial accountability at scale. -
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Diagrams
Diagram as Code for prototyping cloud system architectures
Diagrams lets you draw the cloud system architecture in Python code. It was born for prototyping a new system architecture without any design tools. You can also describe or visualize the existing system architecture as well. Diagram as Code allows you to track the architecture diagram changes in any version control system. Diagrams currently support main major providers including AWS, Azure, GCP, Kubernetes, Alibaba Cloud, Oracle Cloud, etc. It also supports On-Premise nodes, SaaS and major Programming frameworks and languages. ... -
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Torrra
A Python tool that lets you search and download torrents
...Users can add, pause, prioritize, and remove torrents dynamically, while the client intelligently manages piece selection, peer discovery, and bandwidth allocation to optimize download throughput. Torrra also includes hooks for event monitoring and status reporting, enabling third-party tools to visualize torrent progress or integrate with home automation dashboards. -
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GemGIS
Spatial data processing for geomodeling
GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model-building process. Postprocessing of model results will allow export... -
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segment-geospatial
A Python package for segmenting geospatial data with the SAM
The segment-geospatial package draws its inspiration from segment-anything-eo repository authored by Aliaksandr Hancharenka. To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the segment-anything-py and segment-geospatial Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I... -
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whylogs
The open standard for data logging
...With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to track changes in their dataset Create data constraints to know whether their data looks the way it should. Quickly visualize key summary statistics about their datasets. whylogs profiles are the core of the whylogs library. They capture key statistical properties of data, such as the distribution (far beyond simple mean, median, and standard deviation measures), the number of missing values, and a wide range of configurable custom metrics. By capturing these summary statistics, we are able to accurately represent the data and enable all of the use cases described in the introduction. -
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Copulas
A library to model multivariate data using copulas
Copulas is a Python library for modeling multivariate distributions and sampling from them using copula functions. Given a table of numerical data, use Copulas to learn the distribution and generate new synthetic data following the same statistical properties. Choose from a variety of univariate distributions and copulas – including Archimedian Copulas, Gaussian Copulas and Vine Copulas. Compare real and synthetic data visually after building your model. Visualizations are available as 1D... -
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Tauon
The music player of today
Tauon is a modern, streamlined music player app that's packed with features! An emphasis on playlists and drag-and-drop importing puts you in control of your music library. Faded volume control, 24-bit FLAC support, and gapless playback provide the ultimate listening experience. Excellent CUE sheet support, an original smart playlist system, and network playback from koel or Airsonic servers. Last.fm, Listenbrainz, and Maloja scribbling. MPRIS2 support for desktop integration. Tauon is a... -
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Segments.ai
Segments.ai Python SDK
Multi-sensor labeling platform for robotics and autonomous vehicles. The platform for fast and accurate multi-sensor data annotation. Label in-house or with an external workforce. Intuitive labeling interfaces for images, videos, and 3D point clouds (lidar and RGBD). Obtain segmentation labels, vector labels, and more. Our labeling interfaces are set up to label fast and precise. Powerful ML assistance lets you label faster and reduce costs. Integrate data labeling into your existing ML... -
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FiftyOne
The open-source tool for building high-quality datasets
...Nothing hinders the success of machine learning systems more than poor-quality data. And without the right tools, improving a model can be time-consuming and inefficient. FiftyOne supercharges your machine learning workflows by enabling you to visualize datasets and interpret models faster and more effectively. Improving data quality and understanding your model’s failure modes are the most impactful ways to boost the performance of your model. FiftyOne provides the building blocks for optimizing your dataset analysis pipeline. Use it to get hands-on with your data, including visualizing complex labels, evaluating your models, exploring scenarios of interest, identifying failure modes, finding annotation mistakes, and much more! ...
