Best Machine Learning Software for Git

Find and compare the best Machine Learning software for Git in 2025

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

  • 1
    Saturn Cloud Reviews
    Top Pick

    Saturn Cloud

    Saturn Cloud

    $0.005 per GB per hour
    94 Ratings
    Saturn Cloud is an AI/ML platform available on every cloud. Data teams and engineers can build, scale, and deploy their AI/ML applications with any stack.
  • 2
    Inventale Reviews

    Inventale

    Inventale

    $25,000
    Inventale Custom Projects is a UAE-based software development company specializing in unique machine learning and AI-based projects. Combination of software product and project development is our key competitive advantage, that distinguishes us among other companies. We have been helping both market leaders and small businesses and ambitious startups from the USA, the UK, Europe, UAE for over a decade. Inventale has: - an extensive experience in working with major global companies, market leaders, and ambitious startups from the USA, the UK, Europe, and MENA Region; - 20+ clients worldwide, including Majid Al Futtaim, GEMS Education, Central Bank of the UAE, Porsche UAE, Builders, Backlite, Dragoman, B2 Connect, PubMatic, CreativeCo Studio, IQ Data, Convidi, Maxifier, Maxifier, Rambler&Co, Maxima Telecom, CTC Media. - 40+ enthusiastic professionals ready to bring your ideas to life.
  • 3
    Iterative Reviews
    AI teams are faced with challenges that require new technologies. These technologies are built by us. Existing data lakes and data warehouses do not work with unstructured data like text, images, or videos. AI and software development go hand in hand. Built with data scientists, ML experts, and data engineers at heart. Don't reinvent your wheel! Production is fast and cost-effective. All your data is stored by you. Your machines are used to train your models. Existing data lakes and data warehouses do not work with unstructured data like text, images, or videos. New technologies are required for AI teams. These technologies are built by us. Studio is an extension to BitBucket, GitLab, and GitHub. Register for the online SaaS version, or contact us to start an on-premise installation
  • 4
    CognitiveScale Cortex AI Reviews
    To develop AI solutions, engineers must have a resilient, open, repeatable engineering approach to ensure quality and agility. These efforts have not been able to address the challenges of today's complex environment, which is filled with a variety of tools and rapidly changing data. Platform for collaborative development that automates the control and development of AI applications across multiple persons. To predict customer behavior in real-time, and at scale, we can derive hyper-detailed customer profiles using enterprise data. AI-powered models that can continuously learn and achieve clearly defined business results. Allows organizations to demonstrate compliance with applicable rules and regulations. CognitiveScale's Cortex AI Platform is designed to address enterprise AI use cases using modular platform offerings. Customers use and leverage its capabilities in microservices as part of their enterprise AI initiatives.
  • 5
    Amazon SageMaker Studio Lab Reviews
    Amazon SageMaker Studio Lab provides a free environment for machine learning (ML), which includes storage up to 15GB and security. Anyone can use it to learn and experiment with ML. You only need a valid email address to get started. You don't have to set up infrastructure, manage access or even sign-up for an AWS account. SageMaker Studio Lab enables model building via GitHub integration. It comes preconfigured and includes the most popular ML tools and frameworks to get you started right away. SageMaker Studio Lab automatically saves all your work, so you don’t have to restart between sessions. It's as simple as closing your computer and returning later. Machine learning development environment free of charge that offers computing, storage, security, and the ability to learn and experiment using ML. Integration with GitHub and preconfigured to work immediately with the most popular ML frameworks, tools, and libraries.
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