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Published directory entries matching your search.
St. Jude Cloud is a pediatric catastrophic disease data sharing ecosystem created by St. Jude Children's Research Hospital. It provides data and analysis resources to the global research community, including genomic data on pediatric cancers, cancer survivorship and non-cancerous diseases. Its applications cover a genomics platform, a pediatric cancer knowledge base, visualizations, and patient-derived xenograft data.
An open source tool for running arbitrary queries against public data from the Stack Exchange network.
A data and trends page from PeptaHub presenting statistics on peptide compounds, covering legal status, research evidence, administration routes and categories. The page states that 156 peptide profiles were analyzed across 10 therapeutic categories, 5 legal classifications and 6 routes of administration, with the dataset available as JSON and CSV downloads under CC BY 4.0.
Statistics Canada's data portal provides statistical information such as tables, microdata and data visualizations. The listing groups results by type, including tables, profiles of a community or region, and microdata. Users can filter results by subject, geography, frequency and survey or statistical program.
StatsKit.jl is a convenience meta-package for the Julia programming language. Developed by the JuliaStats organization, it aggregates essential packages for statistical computing into a single installation. The project is hosted on GitHub and aims to simplify the setup of a comprehensive statistics environment in Julia.
Statsmodels is a Python package that complements scipy for statistical computations, including descriptive statistics and estimation and inference for statistical models. It provides linear regression models, generalized linear models, discrete models, time series analysis, survival analysis, multivariate methods and a range of statistical tests.
Staying is a code visualization platform for Python, JavaScript and C++. It animates execution flow, traces variables and monitors memory allocation, and offers code optimization suggestions. The documentation collects language support, data-structure examples and runnable code.
Apache Storm is a free and open source distributed realtime computation system. It processes unbounded streams of data and is simple, can be used with any programming language, and integrates with queueing and database technologies. Listed use cases include realtime analytics, online machine learning, continuous computation, distributed RPC and ETL.
Strong is a workout tracker and strength training planner for recording progress in the gym. It offers training planning, progress tracking, and visualization of best sets, max 1RM and body fat percentage with Strong PRO. It is available on iPhone, Android and Apple Watch, and Strong Accounts are free forever.
This is a GPT-2 model fine-tuned on the succinctly/midjourney-prompts dataset of 250k text prompts users issued to Midjourney over a month. It can auto-complete prompts for any text-to-image model, though it occasionally produces Midjourney-specific tags. Users can specify requirements via double-dashed parameters and entity weights.
Summingbird is a library for writing MapReduce programs that resemble native Scala or Java collection transformations and running them on distributed MapReduce platforms including Storm and Scalding. Programs can execute in batch mode, realtime mode, or a hybrid mode combining Scalding and Storm. The repository was archived by its owner on Jan 20, 2022 and is read-only.
A data exploration platform designed to be visual, intuitive, and interactive.
SVGo is a Go language library for SVG generation. It supports common SVG elements including shapes, lines, text, paths, images, and gradients, and is hosted as an open-source project on GitHub.
A Python library for symbolic mathematics.
TechanJS is a library built on D3 for financial charting and technical analysis. It provides visual stock charting, including candlestick, OHLC and indicators, for building interactive financial charts for modern and mobile browsers.
Text To Sql Example Explanation is a Hugging Face Space created by user suriya7. It accepts natural language queries and table details as input, and outputs a corresponding SQL query, sample query results, and an explanation of the generated query.
This Hugging Face Space generates SQL queries from natural language for datasets on Hugging Face; users enter a dataset and a query. The Space is currently paused, and the author can be asked to restart it.
The Analytics Engineering Roundup is a Substack newsletter curating articles on analytics engineering and its adjacent ecosystem, curated by Tristan Handy. He describes analytics engineering as creating and disseminating knowledge within organizations, covering cloud data platforms, dimensional modeling and data quality.
A book by Roger D. Peng and Elizabeth Matsui, dated 2017, about data analysis as an art. It discusses the thought process behind data analysis and covers R software development for building data science tools, including handling complex data, building R packages and custom data visualizations.
The Data Engineering Show is a podcast for data engineering and BI practitioners. It features discussions with tech influencers about practical day-to-day data challenges and solutions. Episodes are available on platforms including Apple Podcasts, Spotify and Pocket Casts.
The Data Science Lifecycle Process is a repeatable, sustainable process for guiding data science teams from initial idea to delivered value. The process is fully documented in the public GitHub repository dslp/dslp.
A personal blog by Chris Said, a data scientist at Propel. The blog is mostly about statistics, technology, and science, and the site links to blog posts on topics such as A/B testing and statistics.
A paid monthly recap newsletter for AI engineers covering December 2023 developments. It frames AI industry activity around four areas: Data Wars, the GPU Rich/Poor War, the Multimodality War, and the RAG/Ops War, and also recaps top items for AI engineers.
The GDELT Project monitors broadcast, print and web news from nearly every country in over 100 languages, identifying people, locations, organizations, themes, sources, emotions, counts, quotes, images and events. Its archives date back to January 1, 1979 and update every 15 minutes. Data can be downloaded as raw CSV files, visualized with the GDELT Analysis Service, or queried with Google BigQuery.
