About

Bokeh makes it simple to create common plots, but also can handle custom or specialized use-cases. Plots, dashboards, and apps can be published in web pages or Jupyter notebooks. Python has an incredible ecosystem of powerful analytics tools: NumPy, Scipy, Pandas, Dask, Scikit-Learn, OpenCV, and more. With a wide array of widgets, plot tools, and UI events that can trigger real Python callbacks, the Bokeh server is the bridge that lets you connect these tools to rich, interactive visualizations in the browser. Microscopium is a project maintained by researchers at Monash University. It allows researchers to discover new gene or drug functions by exploring large image datasets with Bokeh’s interactive tools. Panel is a tool for polished data presentation that utilizes the Bokeh server. It is created and supported by Anaconda. Panel makes it simple to create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.

About

FrameMagic enables you to create awesome photo collages, video collages and video slideshows within just a few seconds with tons of layouts, endless options, colors, patterns, a powerful text editor, beautiful filter effects, flexible play options, music and narrations. FrameMagic also supports powerful and intelligent photo editors including object removal, soft skin, dark light, bokeh, sticker, silhouette, outline, hole, background blur, motion blur and color splash. Combine multiple photos with hundreds of rectangular and polygonal layouts. Blend multiple photos and create a stunning collage. Combine multiple photos into one long. storytelling collage. 3D meshed collage with beautiful mesh layouts.

About

Switch between command and editor modes with a single keystroke. Navigate over cells with arrow keys. Use all of the standard Jupyter shortcuts. Enjoy fully interactive outputs – right under the cell. When editing code cells, enjoy smart code completion, on-the-fly error checking and quick-fixes, easy navigation, and much more. Work with local Jupyter notebooks or connect easily to remote Jupyter, JupyterHub, or JupyterLab servers right from the IDE. Run Python scripts or arbitrary expressions interactively in a Python Console. See the outputs and the state of variables in real-time. Split Python scripts into code cells with the #%% separator and run them individually as you would in a Jupyter notebook. Browse DataFrames and visualizations right in place via interactive controls. All popular Python scientific libraries are supported, including Plotly, Bokeh, Altair, ipywidgets, and others.

About

Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

DevOps teams searching for a visualization library solution

Audience

Users looking for a powerful Photo Editor application that helps create photo collages

Audience

Developers and data science professionals

Audience

Engineers and data scientists requiring a solution to manage and improve their machine learning research

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

$229
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Bokeh
bokeh.org

Company Information

FrameMagic
framemagic.blogspot.com

Company Information

JetBrains
Founded: 2000
Czech Republic
www.jetbrains.com/dataspell/

Company Information

scikit-learn
United States
scikit-learn.org/stable/

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Replicate

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Categories

Categories

Categories

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Amazon Q Developer
Code With Me
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Continue
DagsHub
Databricks Data Intelligence Platform
JavaScript
JetBrains AI Assistant
JetBrains Gateway
Jupyter Notebook
JupyterHub
MLJAR Studio
Markdown
Mistral Code
ModelOp
NumPy
Python
SQL
Supermaven

Integrations

Amazon Q Developer
Code With Me
Codebuddy
Conda
Continue
DagsHub
Databricks Data Intelligence Platform
JavaScript
JetBrains AI Assistant
JetBrains Gateway
Jupyter Notebook
JupyterHub
MLJAR Studio
Markdown
Mistral Code
ModelOp
NumPy
Python
SQL
Supermaven

Integrations

Amazon Q Developer
Code With Me
Codebuddy
Conda
Continue
DagsHub
Databricks Data Intelligence Platform
JavaScript
JetBrains AI Assistant
JetBrains Gateway
Jupyter Notebook
JupyterHub
MLJAR Studio
Markdown
Mistral Code
ModelOp
NumPy
Python
SQL
Supermaven

Integrations

Amazon Q Developer
Code With Me
Codebuddy
Conda
Continue
DagsHub
Databricks Data Intelligence Platform
JavaScript
JetBrains AI Assistant
JetBrains Gateway
Jupyter Notebook
JupyterHub
MLJAR Studio
Markdown
Mistral Code
ModelOp
NumPy
Python
SQL
Supermaven
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