Data Science
Notes
- Data is not always useful and it doesn't matter how much of it you have. There’s no mathematical tool to tell you if your hypothesis is true; you can only see whether it is consistent with the data, and if the data is sparse or unclear, your conclusions are uncertain.
Links
- Cookiecutter Data Science - Logical, reasonably standardized, but flexible project structure for doing and sharing data science work. (Code)
- Pandas - Powerful Python data analysis toolkit. (Ongoing list of pandas quirks) (Manual) (HN) (Pandas Cookbook)
- Datasette - Open source multi-tool for exploring and publishing data. (Web) (datasette-graphql) (Running Datasette on DigitalOcean App Platform) (Interesting ideas in Datasette) (HN)
- Vaex - Out-of-Core DataFrames for Python, visualize and explore big tabular data at a billion rows per second.
- Feather - Fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow.
- ROOT system - Provides a set of OO frameworks with all the functionality needed to handle and analyze large amounts of data in a very efficient way.
- Prefect - New workflow management system, designed for modern infrastructure and powered by the open-source Prefect Core workflow engine.
- Monument - High-productivity toolkit for predictions. AutoML for time series on any desktop, laptop or server.
- Apache Airflow - Platform to programmatically author, schedule, and monitor workflows. (Tutorial) (Kedro-Airflow - Makes it easy to deploy Kedro projects to Airflow.) (Airflow 2.0) (HN) (Introduction to Apache Airflow (2021)) (Customizing Airflow: Beyond Boilerplate Settings)
- Apache Zeppelin - Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
- Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
- Dagster - Data orchestrator for machine learning, analytics, and ETL. (Dagster: The Data Orchestrator) (Lobsters) (Code) (Tweet)
- Google Cloud DataLab - Interactive tools and developer experiences for Big Data on Google Cloud Platform.
- Great Expectations - Leading tool for validating, documenting, and profiling, your data to maintain quality and improve communication between teams. (Code)
- Learn Python for Data Science - Collection of Jupyter Notebooks designed to learn Python for Data Science. (HN)
- Data Engineering Project - Implementation of the data pipeline which consumes the latest news from RSS Feeds and makes them available for users via handy API.
- Hex Technologies - Collaborative data workspace that makes it easy to go from idea to analysis to sharing. Work in SQL and Python notebooks, collaborate live, and publish interactive data apps anyone can use. (Twitter) (Hex 2.0) (Tweet)
- Synerise - Powerful ecosystem driven by Artificial Intelligence with real-time data orchestration created to drive business growth.
- Data Science Lifecycle Process - Set of prescriptive steps and best practices to enable data science teams to consistently deliver value.
- Data Science Lifecycle Base Repo - Template repository for data science projects using the Data Science Life Cycle Process.
- Scalable Data Science - Course sets in big data Using Apache Spark over databricks and their mathematical, statistical and computational foundations using SageMath. (Code)
- Data Carpentry - Develops and teaches workshops on the fundamental data skills needed to conduct research. (GitHub)
- Data Together Research - Research for tackling the general problem of data resilience & interactivity in all its forms.
- Elements of Data Science - Introduction to data science in Python, for people with no programming experience. (Code)
- Tably - Lightning fast exploration, search and analytics, with an intuitive UI and supercharged formula.
- Knowledge Repo - Curated knowledge sharing platform for data scientists and other technical professions.
Last modified 10d ago