Open-source data science application
DIY
The MySQMProESP32 project on SourceForge offers a DIY sky quality and weather station, powered by the ESP32 microcontroller. It allows users to monitor sky quality, weather conditions, and other environmental metrics, such as temperature, humidity, and cloud coverage. This station supports multiple sensors, GPS functionality, and web-based data logging. The
Statistics
StatsPro is a comprehensive tool designed to help scientists detect differentially expressed proteins in label-free quantitative proteomics experiments. The tool integrates 12 common statistical methods and 6 P-value combination strategies, allowing users to systematically evaluate the performance of these methods. By offering three evaluation criteria, StatsPro provides a detailed and
Statistics
SPSS (Statistical Package for the Social Sciences) is a powerful software widely used for statistical analysis in social science research, healthcare, marketing, and various academic fields. It provides tools for performing complex data analysis such as descriptive statistics, ANOVA, regression, factor analysis, and more. SPSS offers an intuitive interface for
BioInformatics
The Python programming language plays a significant role in data science, AI, bioinformatics, web development, desktop applications, and game development. Python has gained popularity as an easy-to-learn language with a gentle learning curve and powerful frameworks. This has made it a favorite for university student projects and a common first
BioInformatics
As Natural Language Processing (NLP) evolves, researchers and developers continually seek new frameworks to boost efficiency, speed, and performance. Ascle, an innovative NLP framework developed by Yale LILY (Language, Information, and Learning at Yale), stands out as one of the most promising new entries in this field. This Free open-source
research
MedCodes is a powerful Python package that simplifies the standardization and interpretation of clinical data. Whether you're working with drug classifications or extracting meaningful medical insights, MedCodes provides the tools to navigate complex medical coding systems. A key feature of MedCodes is its integration with RxNorm, a system
EMR
Healthcare researchers and data scientists often grapple with processing vast amounts of complex, sensitive Electronic Health Records (EHR) data. EHrapy, an open-source Python package developed by TheisLab, tackles these challenges head-on. It streamlines the handling, analysis, and exploration of healthcare data—especially EHR data—in a privacy-preserving and user-friendly manner.
ocr
In academia, research, and scientific fields, LaTeX has long been the preferred markup language for creating complex mathematical formulas and professional-grade documentation. However, converting printed or scanned documents containing LaTeX code back into an editable format can be challenging. Enter LaTeX-OCR, an open-source project designed to tackle this problem. What
Big Data
In today's data-driven world, efficiently managing and storing vast amounts of structured and semi-structured data is crucial. Apache Parquet, an open-source columnar storage format, has emerged as a go-to solution for big data frameworks. Designed to handle large-scale data processing efficiently, Parquet is particularly useful for analytics and
Open-source
Universities have long been at the forefront of technological innovation, consistently pushing the boundaries of what's possible in various fields. In recent years, the trend of releasing open-source projects has become an integral part of academic contributions, revolutionizing the way knowledge is shared and applied. Throughout 2023 and
data science
Transform Data into Interactive Dashboards with Observable Framework
Python
Python is a top choice for building data applications due to its versatility, ease of use, and strong ecosystem of libraries. For data scientists and business developers, Python offers powerful tools for data analysis, machine learning, and data visualization, making it ideal for tackling complex data science projects and delivering
data science
Evidence is an open-source, code-based alternative to drag-and-drop business intelligence tools. It is a lightweight framework for building data apps. It's open source and free to get started. Evidence can be easily self-hosted at Netlify, Vercel or even your own server. Generate a Feature-rich website Evidence generates a
Python
For Python developers, mastering these visualization tools can significantly enhance their skill set, making them more valuable in the job market and enabling them to tackle a broader range of data-driven projects. Benefits of Data Visualization for Python Projects, Data Science, and Analytics: 1. Enhanced Data Understanding: Visualizations simplify complex
data science
Mercury is a free and open-source app that allows you to add interactive widgets in Python notebooks, so you can share notebooks as web applications. Mercury offers a set of widgets with simple re-execution of cells. Features * Easy to use * add widgets with Python code - no frontend experience needed!
data science
Streamlit is an open-source Python self-hosted platform that makes it incredibly easy to create and share web applications for machine learning and data science. With Streamlit, you can transform data scripts into interactive web apps in just a few minutes, without needing to have deep expertise in web development. You
data engineering
What is ArchieML? ArchieML (Archie Markup Language) is a simple and human-readable markup language designed for managing content in a structured format. It was developed by the Interactive News team at The New York Times to simplify the process of working with structured data in a way that is easy
Python
Python is a versatile programming language known for its simplicity and readability, making it a popular choice for various applications, including GUI desktop apps. With libraries like Tkinter, PyQt, and PySide, developers can create cross-platform graphical user interfaces that are both functional and visually appealing. Tkinter, included with Python, is
Rust
Rust, a systems programming language, is gaining traction in various fields, including data science. Rust is known for its performance, safety, and concurrency capabilities, Rust offers several advantages for data engineering, databases, real-time data processing, and data analytics. Why Rust? Rust is designed to be fast and reliable, making it
Pathology
Digital pathology is a cutting-edge field that transforms traditional pathology by digitizing glass slides into high-resolution whole slide images (WSIs). These WSIs capture the entire tissue sample on a slide, enabling detailed analysis and diagnostics through digital means. By using advanced imaging techniques, digital pathology allows pathologists to view, analyze,
mathematic
Mathematics apps are essential tools used by engineers, scientists, educators, and researchers to perform complex calculations, simulations, and data analysis. These applications provide functionalities like symbolic computation, numerical analysis, data visualization, and more. Professionals in academia, industry, and research rely on these tools for tasks ranging from simple calculations to
data science
Data engineering is the backbone of any data-driven project. With the right tools, you can streamline your data workflows, from collection and transformation to storage and retrieval. Julia, known for its high performance and ease of use, offers a plethora of packages tailored for data engineering tasks. Getting Started with
Tutorials
Data visualization is an essential aspect of data analysis, enabling you to understand and communicate your data's underlying patterns and insights. Julia offers several powerful packages for creating various types of visualizations, from basic plots to complex interactive charts. In this tutorial will introduce you to some of
programming
Julia is a high-level, high-performance programming language developed specifically for numerical and scientific computing. Launched in 2012, it combines the ease of use of Python with the speed of C. Julia's design revolves around performance, with a just-in-time (JIT) compiler, allowing it to execute code efficiently. While Julia