5 مستودعات
Tools for performing data analysis within executable documents.
Distinguishing note: Focuses on the interactive workflow rather than static data processing.
Explore 5 awesome GitHub repositories matching data & databases · Interactive Data Science. Refine with filters or upvote what's useful.
This project is an interactive educational textbook and comprehensive machine learning resource designed for deep learning education. It provides a structured curriculum that combines narrative prose with executable code, utilizing literate programming to create reproducible learning experiences within a collection of Jupyter Notebooks. The repository distinguishes itself by teaching machine learning through applied research and modular design. It demonstrates a callback-driven training loop, a declarative data-block pipeline, and a layered abstraction API that allows users to transition betw
Enables interactive data analysis through live code and visual outputs.
This project provides a full Python interpreter compiled to WebAssembly, enabling the execution of Python code and scientific libraries directly within web browsers and server-side environments. By bridging the gap between language runtimes, it allows developers to run computational tasks, manage packages, and perform data analysis in client-side environments without requiring a backend server. The platform distinguishes itself through a comprehensive foreign function interface that enables bidirectional data exchange, object proxying, and function calling between Python and JavaScript. It in
Enables interactive data analysis and computational notebooks that perform heavy processing locally.
This project is a comprehensive collection of machine learning educational resources, featuring a Python-based curriculum, study guides for deep learning, and a specialized knowledge base for machine learning operations. It provides structured learning paths that guide users from foundational programming through to advanced neural network implementations. The repository focuses on interactive learning by providing a directory of executable notebooks and cloud-hosted experiments. It maps theoretical research papers and textbooks to practical code implementations and maintains a curated directo
Enables iterative data analysis and machine learning experimentation within executable notebook documents.
Spyder is a scientific integrated development environment designed for scientific computing and interactive Python programming. It functions as a static analysis code editor and an interactive Python console, providing a specialized environment for writing and analyzing code for science and engineering. The platform distinguishes itself as an extensible development tool, utilizing a modular plugin architecture that allows for the addition of custom features or the embedding of core components into other software. It features a dedicated debugger and profiler for tracing code execution and mea
Provides an interactive workflow for executing code in cells or lines to analyze data and inspect runtime variables.
This project is an educational resource and a collection of instructional materials for performing data manipulation and statistical analysis using Python. It provides a comprehensive set of guides and code examples for using the Pandas, NumPy, and Matplotlib libraries to analyze structured data. The resource includes a dedicated guide for reshaping, cleaning, and aggregating tabular data and time series via Pandas, alongside a reference for high-performance vectorized operations and linear algebra using NumPy. It also features tutorials for creating publication-quality charts, distribution p
Facilitates an interactive data science workflow using executable documents for iterative analysis and debugging.