Best Application Development Software for VESSL AI

Find and compare the best Application Development software for VESSL AI in 2024

Use the comparison tool below to compare the top Application Development software for VESSL AI on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Google Cloud Platform Reviews
    Top Pick

    Google Cloud Platform

    Google

    Free ($300 in free credits)
    55,132 Ratings
    See Software
    Learn More
    Google Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging.
  • 2
    Kubernetes Reviews
    Kubernetes (K8s), an open-source software that automates deployment, scaling and management of containerized apps, is available as an open-source project. It organizes containers that make up an app into logical units, which makes it easy to manage and discover. Kubernetes is based on 15 years of Google's experience in running production workloads. It also incorporates best-of-breed practices and ideas from the community. Kubernetes is built on the same principles that allow Google to run billions upon billions of containers per week. It can scale without increasing your operations team. Kubernetes flexibility allows you to deliver applications consistently and efficiently, no matter how complex they are, whether you're testing locally or working in a global enterprise. Kubernetes is an open-source project that allows you to use hybrid, on-premises, and public cloud infrastructures. This allows you to move workloads where they are most important.
  • 3
    Jupyter Notebook Reviews
    Open-source web application, the Jupyter Notebook, allows you to create and share documents with live code, equations, and visualizations. Data cleaning and transformation, numerical modeling, statistical modeling and data visualization are just a few of the many uses.
  • 4
    Visual Studio Code Reviews
    Top Pick
    Code editing. Redefined Free. Open source. It runs everywhere. IntelliSense provides smart completions that go beyond syntax highlighting and autocomplete. It uses variable types, function definitions and imported modules to provide intelligent completions. You can debug code directly from the editor. You can attach or launch your apps, and debug with breakpoints, call stacks and an interactive console. It's never been easier to work with Git or other SCM providers. The editor allows you to review diffs and stage files, as well as make commits. Pull and push from any hosted SCM service. Want even more features? To add languages, themes, debuggers and connect to other services, install extensions. Extensions are separate processes that don't slow down your editor. Learn more about extensions. Microsoft Azure allows you to deploy and host your React (Angular), Vue, Node (and many more!) applications. Sites can store and query relational or document-based data and scale with serverless computing.
  • 5
    LangChain Reviews
    We believe that the most effective and differentiated applications won't only call out via an API to a language model. LangChain supports several modules. We provide examples, how-to guides and reference docs for each module. Memory is the concept that a chain/agent calls can persist in its state. LangChain provides a standard interface to memory, a collection memory implementations and examples of agents/chains that use it. This module outlines best practices for combining language models with your own text data. Language models can often be more powerful than they are alone.
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