Best Development Frameworks for Freelancers

.NET Multi-platform App UI (.NET MAUI) is a framework for building modern, multi-platform, natively compiled iOS, Android, macOS, and Windows apps using C# and XAML in a single codebase. .NET MAUI uses the latest, modern technologies for building native apps on Android, iOS, macOS, and Windows abstracting them into one common framework built on .NET 6. Native apps look and feel like the operating system on which they belong by default and layouts are fully adapted to each device automatically with no additional code. Platform APIs are available directly from C# to access over 60 platform features from a single cross-platform API including access to things like isolated storage, sensors, geolocation, camera, and a whole lot more with no compromises.

jQuery Mobile is an HTML5-based user interface system designed to make responsive websites and apps that are accessible on all smartphones, tablets, and desktop devices. jQuery Mobile framework takes the "write less, do more" mantra to the next level: Instead of writing unique applications for each mobile device or OS, the jQuery mobile framework allows you to design a single highly-branded responsive website or application that will work on all popular smartphone, tablet, and desktop platforms. We believe that your website or app should feel like your brand, not any particular OS. To make building highly customized themes easy, we've created ThemeRoller for mobile to make it easy to drag and drop colors and download a custom theme. For polished visuals without the bloat, we leverage CSS3 properties. We recommend using our tool to build a custom bundle that contains only the components you need.

Vaadin is a web app development platform for Java. It helps you build reliable web apps with great UX faster than before. Building an enterprise web app involves a lot of moving pieces. Vaadin simplifies the process with an integrated web app development platform for Java backends. Vaadin comes with all the components, frameworks, and tools you need to build a reliable, secure, app with great UX. Research shows that good user experience (UX) increases employee engagement, helps digital transformations to succeed, and avoids costly mistakes. The Vaadin Design System provides UI components and UX patterns that help you build consistently good user experiences in every app. Better yet, you can use it to build a custom design system for your organization. Vaadin comes with 45+ UI components that help you build consistent UIs fast. The theme can be customized to match your brand. Vaadin components work with screen readers and assistive devices.

Helidon is a cloud-native, open‑source set of Java libraries for writing microservices that run on a fast web core powered by Netty. Helidon Níma is the first Java microservices framework based on virtual threads. Helidon is designed to be simple to use, with tooling and examples to get you going quickly. Since Helidon is simply a collection of Java libraries running on a fast Netty core, there is no extra overhead or bloat. Helidon supports MicroProfile and provides familiar APIs like JAX-RS, CDI, and JSON-P/B. Our implementation runs on our fast Helidon Reactive WebServer. Helidon Reactive WebServer provides a modern functional programming model and runs on top of Netty. Lightweight, flexible, and reactive, the Helidon WebServer provides a simple-to-use and fast foundation for your microservices. With support for health checks, metrics, tracing, and fault tolerance, Helidon has what you need to write cloud-ready applications that integrate with Prometheus, Jaeger/Zipkin, etc.

Apache Mahout is a powerful, scalable, and versatile machine learning library designed for distributed data processing. It offers a comprehensive set of algorithms for various tasks, including classification, clustering, recommendation, and pattern mining. Built on top of the Apache Hadoop ecosystem, Mahout leverages MapReduce and Spark to enable data processing on large-scale datasets. Apache Mahout(TM) is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms. Apache Spark is the recommended out-of-the-box distributed back-end or can be extended to other distributed backends. Matrix computations are a fundamental part of many scientific and engineering applications, including machine learning, computer vision, and data analysis. Apache Mahout is designed to handle large-scale data processing by leveraging the power of Hadoop and Spark.

Laminas is the enterprise-ready PHP framework and components. Components for any PHP application, include dependency injection, event dispatchers, input validation and filtering, pagination and navigation, feed generation and parsing, and much, much more. Build PHP middleware applications, using the PSR-7 and PSR-15 specifications, using a variety of routing and templating options, and the dependency injection container you prefer. Build RESTful APIs using standards and provide validation, authentication, authorization, and versioning right out of the box. A proven history of success running business critical and high-usage applications, ready for PHP 7. Laminas is built with security best practices. Store passwords and encrypt with AES-256. Engineered with performance tuning in mind, Laminas runs up to 4x faster than version 2 releases. Laminas API tools provide JSON representations that can be parsed and used in any mobile framework.

Core ML applies a machine learning algorithm to a set of training data to create a model. You use a model to make predictions based on new input data. Models can accomplish a wide variety of tasks that would be difficult or impractical to write in code. For example, you can train a model to categorize photos or detect specific objects within a photo directly from its pixels. After you create the model, integrate it in your app and deploy it on the user’s device. Your app uses Core ML APIs and user data to make predictions and to train or fine-tune the model. You can build and train a model with the Create ML app bundled with Xcode. Models trained using Create ML are in the Core ML model format and are ready to use in your app. Alternatively, you can use a wide variety of other machine learning libraries and then use Core ML Tools to convert the model into the Core ML format. Once a model is on a user’s device, you can use Core ML to retrain or fine-tune it on-device.