Showing 5 open source projects for "utility"

View related business solutions
  • Go From AI Idea to AI App Fast Icon
    Go From AI Idea to AI App Fast

    One platform to build, fine-tune, and deploy ML models. No MLOps team required.

    Access Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
    Try Free
  • $300 in Free Credit Towards Top Cloud Services Icon
    $300 in Free Credit Towards Top Cloud Services

    Build VMs, containers, AI, databases, storage—all in one place.

    Start your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
    Get Started
  • 1
    PyTorch

    PyTorch

    Open source machine learning framework

    ...PyTorch consists of torch (Tensor library), torch.autograd (tape-based automatic differentiation library), torch.jit (a compilation stack [TorchScript]), torch.nn (neural networks library), torch.multiprocessing (Python multiprocessing), and torch.utils (DataLoader and other utility functions). PyTorch can be used as a replacement for Numpy, or as a deep learning research platform that provides optimum flexibility and speed.
    Downloads: 71 This Week
    Last Update:
    See Project
  • 2
    PyTorch/XLA

    PyTorch/XLA

    Enabling PyTorch on Google TPU

    PyTorch/XLA is a Python package that uses the XLA deep learning compiler to connect the PyTorch deep learning framework and Cloud TPUs. You can try it right now, for free, on a single Cloud TPU with Google Colab, and use it in production and on Cloud TPU Pods with Google Cloud. Take a look at one of our Colab notebooks to quickly try different PyTorch networks running on Cloud TPUs and learn how to use Cloud TPUs as PyTorch devices. We are also introducing new TPU VMs for more transparent...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    Deep Learning Models

    Deep Learning Models

    A collection of various deep learning architectures, models, and tips

    This repository collects clear, well-documented implementations of deep learning models and training utilities written by Sebastian Raschka. The code favors readability and pedagogy: components are organized so you can trace data flow through layers, losses, optimizers, and evaluation. Examples span fundamental architectures—MLPs, CNNs, RNN/Transformers—and practical tasks like image classification or text modeling. Reproducible training scripts and configuration files make it...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 4
    NLP Best Practices

    NLP Best Practices

    Natural Language Processing Best Practices & Examples

    ...Data scientists started moving from traditional methods to state-of-the-art (SOTA) deep neural network (DNN) algorithms which use language models pretrained on large text corpora. This repository contains examples and best practices for building NLP systems, provided as Jupyter notebooks and utility functions. The focus of the repository is on state-of-the-art methods and common scenarios that are popular among researchers and practitioners working on problems involving text and language. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in NLP algorithms, neural architectures, and distributed machine learning systems.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
    Try Free
  • 5
    MatlabFunc

    MatlabFunc

    Matlab codes for feature learning

    MatlabFunc is a collection of MATLAB functions developed by the ZJULearning group to support various tasks in computer vision, machine learning, and numerical computation. The repository brings together a wide range of utility scripts, algorithms, and implementations that serve as building blocks for research and development. These functions cover areas such as matrix operations, optimization, data processing, and visualization, making them broadly applicable across different research domains. The project is intended to provide reusable and adaptable MATLAB code that can save time for researchers and students working on experimental or applied projects. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB