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github.com

PipeRider is a tool described as code review for data in dbt. It compares data to highlight differences in impacted downstream dbt models, profiles dbt models, and generates a static HTML report each run. The project states that PipeRider has been superseded by Recce and will no longer be updated on a regular basis.

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github.com

PyCM is a multi-class confusion matrix library written in Python. It supports input data vectors and direct matrices and offers post-classification model evaluation statistics. It is aimed at data scientists needing metrics for predictive models and classifiers. A MATLAB setup is also documented.

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github.com

The repository holds materials and IPython notebooks for "Python for Data Analysis, 3rd Edition" by Wes McKinney, published by O'Reilly Media. Notebooks cover chapters on Python basics, NumPy, pandas, data loading, cleaning, visualization, time series and modeling libraries, plus appendices. The code is released under the MIT license.

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github.com

Skale is a distributed data processing and machine learning engine that provides a high-level API in JavaScript and a parallel execution engine on top of Node.js. The repository was archived by its owner on May 29, 2021 and is read-only. It supports multiple data sources and formats, and can run in local or distributed mode.

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github.com

Snorkel is a system for quickly generating training data with weak supervision, released under an Apache-2.0 license and written in Python. The project started at Stanford in 2015 to programmatically label, build, and manage training data. The team now focuses on Snorkel Flow, an end-to-end AI application development platform based on the core ideas behind Snorkel.

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github.com

Tonic is a tool for downloading, manipulating and loading event-based or spike-based data, described as similar to PyTorch Vision but for neuromorphic data. It provides event datasets and transformations, and the project states it is looking for a new maintainer.

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github.com

Upgini is an open-source data search and enrichment library for Machine Learning and AI pipelines. It enables users to find and add relevant features from hundreds of public and premium external data sources, including open and commercial large language models.

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Open CC-BY-4.0 dataset of evidence-graded dietary-supplement data covering dosing, bioavailability, drug-nutrient interactions and cost-per-effective-dose, with every clinical claim tied to a PubMed PMID. Compiled by Verified Supplement Data, it is mirrored on Hugging Face and Kaggle and offered as a free live JSON API.

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Open-source project that applies AI to data analysis, extraction, visualization, or business intelligence.

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github.com

AI Models Catalog is a structured YAML catalog of AI model providers and their models, sourced from first-party APIs and official documentation. It includes TypeScript type definitions and Zod runtime validation schemas, plus scripts to sync data from providers and validate YAML files against schemas.

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github.com

Airbyte is an open-source data movement platform for ELT pipelines and AI agents. It transfers data from APIs, databases, and files to data warehouses, data lakes, and AI applications. The platform is available for self-hosted deployment and as a cloud service.

File Hosting & Sharing 0
github.com

Open-source project that applies AI to data analysis, extraction, visualization, or business intelligence.

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github.com

AutoViz is a Python library that automatically visualizes any dataset, any size, with a single line of code. It also offers the FixDQ() function for a quick assessment of dataset quality and fixing data quality issues. The project aims to provide an automated approach to exploratory data analysis through quick and easy data visualization plus data quality, abstracting away the complexities of various plotting libraries and techniques.

Models & Machine Learning 0
github.com

CPU and GPU-accelerated matrix library intended to support large-scale exploratory data analysis.

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github.com

NumPy and Pandas interface to Big Data.

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github.com

Bowtie is a library for writing dashboards in Python. It wraps the code needed for interactive data exploration and visualization, so users can build functionality without knowing web frameworks or JavaScript. It can be installed with conda or pip, and Docker images are provided.

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github.com

Cerberus is a lightweight and extensible data validation library for Python. It provides type checking and other base functionality out of the box, is designed to be non-blocking and extensible for custom validation, and has no dependencies. It is available on PyPI and maintained according to semantic versioning since version 1.2.

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github.com

The College ROI Dataset provides the 30-year net present value of U.S. colleges and majors. It is derived from FREOPP, IPEDS, and BEA data and is released under a CC BY 4.0 license. The dataset is maintained by le-teen.com.

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github.com

d3py is a plotting library for Python based on D3. It builds on d3.js and the pandas DataFrame module to plot data from the command line or simple scripts into a browser window. Its README describes the code as an experiment, notes that it is not actively developed, and points to vincent as an alternative.

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github.com

Dash is an open-source Python library for building data applications and dashboards without requiring JavaScript expertise. It is maintained by Plotly and hosted on the company's public GitHub repository, where users can access source code and contribute to the project.

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github.com

A lightweight framework for data analysis in JavaScript.

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github.com

Collect, clean and visualize your data in Python.

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github.com

An agentic LLM for autonomous data science that performs data preparation, analysis, modeling, visualization, and report generation without human intervention. It supports open-ended research on structured, semi-structured, and unstructured data sources, and the model, code, training data, and demo are open-sourced.

Models & Machine Learning 0
github.com

Deepchecks is an open-source project for validating machine learning models and data from research to production. It includes built-in and custom checks and suites for tabular, NLP and CV validation, CI and testing management, and monitoring of deployed models. Installation is via pip.

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