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What is jQuery Mobile?

jQuery Mobile is an HTML5-based user interface framework designed to develop responsive websites and applications that operate flawlessly on smartphones, tablets, and desktop computers. It enhances the philosophy of "write less, do more" by enabling developers to build a single, unified, and brand-centric responsive website or application rather than having to create separate iterations for different mobile devices or operating systems. Our approach highlights the importance of ensuring that a website or application reflects your brand identity instead of adhering to the traits of any particular operating system. To support the development of highly customized themes, we provide ThemeRoller for mobile, which streamlines the customization of colors and the downloading of personalized themes through an intuitive drag-and-drop interface. Furthermore, we leverage CSS3 properties to create visually striking designs while avoiding unnecessary bloat. For maximum efficiency and performance, we recommend utilizing our tool to assemble a custom bundle that includes only the necessary components for your project, thereby ensuring a smooth and focused experience. By doing so, developers can concentrate on their distinctive branding while simultaneously delivering a flexible user experience that meets the needs of a diverse audience. This approach ultimately fosters creativity and innovation within the development process, empowering creators to push the boundaries of their designs.

What is Core ML?

Core ML makes use of a machine learning algorithm tailored to a specific dataset to create a predictive model. This model facilitates predictions based on new incoming data, offering solutions for tasks that would be difficult or unfeasible to program by hand. For example, you could create a model that classifies images or detects specific objects within those images by analyzing their pixel data directly. After the model is developed, it is crucial to integrate it into your application and ensure it can be deployed on users' devices. Your application takes advantage of Core ML APIs and user data to enable predictions while also allowing for the model to be refined or retrained as needed. You can build and train your model using the Create ML application included with Xcode, which formats the models for Core ML, thus facilitating smooth integration into your app. Alternatively, other machine learning libraries can be utilized, and Core ML Tools can be employed to convert these models into the appropriate format for Core ML. Once the model is successfully deployed on a user's device, Core ML supports on-device retraining or fine-tuning, which improves its accuracy and overall performance. This capability not only enhances the model based on real-world feedback but also ensures that it remains relevant and effective in various applications over time. Continuous updates and adjustments can lead to significant advancements in the model's functionality.

Media

Media

Integrations Supported

Apple tvOS
Apple watchOS
Xcode

Integrations Supported

Apple tvOS
Apple watchOS
Xcode

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

OpenJS Foundation

Date Founded

2019

Company Location

United States

Company Website

jquerymobile.com

Company Facts

Organization Name

Apple

Company Location

United States

Company Website

developer.apple.com/documentation/coreml

Categories and Features

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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