Lumio
Lumio is a web-based learning platform that offers more ways to effortlessly make learning fun and engaging on student devices.
Teachers can start from scratch, or import existing content like PDFs, Google Slides, PowerPoints, and Canva designs and transform them into dynamic, engaging learning experiences on any device. Within Lumio, they can mix and match file types and add interactive elements like games, collaborative whiteboards, handouts, and assessments, all from a single place. Teachers can even share content with colleagues through shared libraries and co-edit lessons in real-time to leverage one another’s classroom experiences.
Tools like instructional audio, activity dashboards, and the ability to offer real-time feedback make Lumio a one-stop shop for teachers. It allows them to personalize learning, enable student creation, and gain insight into learning.
Not only does Lumio offer more ways to engage students, it’s also specifically designed to improve outcomes – it’s not just fun, it works! With the Research-Based Design Certification from Digital Promise, educators and administrators can feel confident in the benefits of using Lumio.
With 3 available plan options, there’s an option for everyone.
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Highcharts
Highcharts, a Javascript-based charting library, makes it easy to add interactive charts and graphs to web or mobile projects of any size.
Highcharts is used by more than 80% of the 100 biggest companies in the world, as well as thousands of developers from a variety of industries, including finance, publishing, application development, and data science.
Highcharts is in active development since 2009. It remains a favorite among developers due to its robust feature set and ease-of-use documentation, accessibility features and vibrant community.
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Bokeh
Bokeh simplifies the creation of standard visualizations while also accommodating unique or specialized scenarios. It allows users to publish plots, dashboards, and applications seamlessly on web pages or within Jupyter notebooks. The Python ecosystem boasts a remarkable collection of robust analytical libraries such as NumPy, Scipy, Pandas, Dask, Scikit-Learn, and OpenCV. With its extensive selection of widgets, plotting tools, and user interface events that can initiate genuine Python callbacks, the Bokeh server serves as a vital link, enabling the integration of these libraries into dynamic, interactive visualizations accessible via the browser. Additionally, Microscopium, a project supported by researchers at Monash University, empowers scientists to uncover new functions of genes or drugs through the exploration of extensive image datasets facilitated by Bokeh’s interactive capabilities. Another useful tool, Panel, which is developed by Anaconda, enhances data presentation by leveraging the Bokeh server. It streamlines the creation of custom interactive web applications and dashboards by linking user-defined widgets to a variety of elements, including plots, images, tables, and textual information, thus broadening the scope of data interaction possibilities. This combination of tools fosters a rich environment for data analysis and visualization, making it easier for researchers and developers to share their insights.
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marimo
Introducing an innovative reactive notebook designed for Python, which allows you to conduct repeatable experiments, run scripts seamlessly, launch applications, and manage versions using git.
🚀 Comprehensive: it serves as a substitute for jupyter, streamlit, jupytext, ipywidgets, papermill, and additional tools.
⚡️ Dynamic: when you execute a cell, marimo automatically runs all related cells or flags them as outdated.
🖐️ Engaging: easily connect sliders, tables, and plots to your Python code without the need for callbacks.
🔬 Reliable: ensures no hidden states, guarantees deterministic execution, and includes built-in package management for consistency.
🏃 Functional: capable of being executed as a Python script, allowing for customization via CLI arguments.
🛜 Accessible: can be transformed into an interactive web application or presentation, and functions in the browser using WASM.
🛢️ Tailored for data: efficiently query dataframes and databases using SQL, plus filter and search through dataframes effortlessly.
🐍 git-compatible: stores notebooks as .py files, making version control straightforward.
⌨️ A contemporary editor: features include GitHub Copilot, AI helpers, vim keybindings, a variable explorer, and an array of other enhancements to streamline your workflow.
With these capabilities, this notebook elevates the way you work with Python, promoting a more efficient and collaborative coding environment.
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