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    Easily Host LLMs and Web Apps on Cloud Run

    Run everything from popular models with on-demand NVIDIA L4 GPUs to web apps without infrastructure management.

    Run frontend and backend services, batch jobs, host LLMs, and queue processing workloads without the need to manage infrastructure. Cloud Run gives you on-demand GPU access for hosting LLMs and running real-time AI—with 5-second cold starts and automatic scale-to-zero so you only pay for actual usage. New customers get $300 in free credit to start.
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    Cut Cloud Costs with Google Compute Engine

    Save up to 91% with Spot VMs and get automatic sustained-use discounts. One free VM per month, plus $300 in credits.

    Save on compute costs with Compute Engine. Reduce your batch jobs and workload bill 60-91% with Spot VMs. Compute Engine's committed use offers customers up to 70% savings through sustained use discounts. Plus, you get one free e2-micro VM monthly and $300 credit to start.
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    Machine Learning PyTorch Scikit-Learn

    Machine Learning PyTorch Scikit-Learn

    Code Repository for Machine Learning with PyTorch and Scikit-Learn

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    Downloads: 1 This Week
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    Google Research Football

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    Check out the new game server

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    Downloads: 0 This Week
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    Trax

    Trax

    Deep learning with clear code and speed

    ...Features and resources, API docs, where to talk to us, how to open an issue and more. Walkthrough, how Trax works, how to make new models and train on your own data. Trax includes basic models (like ResNet, LSTM, Transformer) and RL algorithms (like REINFORCE, A2C, PPO). It is also actively used for research and includes new models like the Reformer and new RL algorithms like AWR. Trax has bindings to a large number of deep learning datasets, including Tensor2Tensor and TensorFlow datasets. You can use Trax either as a library from your own python scripts and notebooks or as a binary from the shell, which can be more convenient for training large models. ...
    Downloads: 2 This Week
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  • 4
    ReinforcementLearningAnIntroduction.jl

    ReinforcementLearningAnIntroduction.jl

    Julia code for the book Reinforcement Learning An Introduction

    This project provides the Julia code to generate figures in the book Reinforcement Learning: An Introduction(2nd). One of our main goals is to help users understand the basic concepts of reinforcement learning from an engineer's perspective. Once you have grasped how different components are organized, you're ready to explore a wide variety of modern deep reinforcement learning algorithms in ReinforcementLearningZoo.jl.
    Downloads: 0 This Week
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  • Go from Data Warehouse to Data and AI platform with BigQuery Icon
    Go from Data Warehouse to Data and AI platform with BigQuery

    Build, train, and run ML models with simple SQL. Automate data prep, analysis, and predictions with built-in AI assistance from Gemini.

    BigQuery is more than a data warehouse—it's an autonomous data-to-AI platform. Use familiar SQL to train ML models, run time-series forecasts, and generate AI-powered insights with native Gemini integration. Built-in agents handle data engineering and data science workflows automatically. Get $300 in free credit, query 1 TB, and store 10 GB free monthly.
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  • 5
    Spinning Up in Deep RL

    Spinning Up in Deep RL

    Educational resource to help anyone learn deep reinforcement learning

    Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the...
    Downloads: 0 This Week
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