Showing 4 open source projects for "programming without coding"

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  • Gen AI apps are built with MongoDB Atlas Icon
    Gen AI apps are built with MongoDB Atlas

    Build gen AI apps with an all-in-one modern database: MongoDB Atlas

    MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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  • Orchestrate Your AI Agents with Zenflow Icon
    Orchestrate Your AI Agents with Zenflow

    The multi-agent workflow engine for modern teams. Zenflow executes coding, testing, and verification with deep repo awareness

    Zenflow orchestrates AI agents like a real engineering system. With parallel execution, spec-driven workflows, and deep multi-repo understanding, agents plan, implement, test, and verify end-to-end. Upgrade to AI workflows that work the way your team does.
    Try free now
  • 1
    Thinc

    Thinc

    A refreshing functional take on deep learning

    Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy.
    Downloads: 0 This Week
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  • 2
    AWS Neuron

    AWS Neuron

    Powering Amazon custom machine learning chips

    AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can...
    Downloads: 0 This Week
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  • 3
    CodeContests

    CodeContests

    Large dataset of coding contests designed for AI and ML model training

    CodeContests, developed by Google DeepMind, is a large-scale competitive programming dataset designed for training and evaluating machine learning models on code generation and problem solving. This dataset played a central role in the development of AlphaCode, DeepMind’s model for solving programming problems at a human-competitive level, as published in Science. CodeContests aggregates problems and human-written solutions from multiple programming competition platforms, including AtCoder,...
    Downloads: 1 This Week
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  • 4
    Stanford Machine Learning Course

    Stanford Machine Learning Course

    machine learning course programming exercise

    ...The exercises serve as practical, hands-on reinforcement of theoretical concepts taught in the course. This collection is valuable for students and practitioners who want to strengthen their skills in machine learning through coding exercises.
    Downloads: 0 This Week
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  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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