Showing 3 open source projects for "statistical learning"

View related business solutions
  • Earn up to 16% annual interest with Nexo. Icon
    Earn up to 16% annual interest with Nexo.

    Access competitive interest rates on your digital assets.

    Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform. Geographic restrictions, eligibility, and terms apply.
    Get started with Nexo.
  • Ship Agents Faster Icon
    Ship Agents Faster

    Transform your applications and workflows into powerful agentic systems at global scale.

    Gemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
    Start Free
  • 1
    NBA Sports Betting Machine Learning

    NBA Sports Betting Machine Learning

    NBA sports betting using machine learning

    ...Using this dataset, the project constructs matchup features that represent team performance trends and contextual information about each game. Machine learning models are then trained to estimate the probability that a team will win a game as well as whether the total score will fall above or below the sportsbook’s predicted total. In addition to predicting outcomes, the project evaluates expected value to determine whether a potential bet offers a statistical advantage compared with sportsbook odds.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 2
    Synthetic Data Generator

    Synthetic Data Generator

    SDG is a specialized framework

    Synthetic Data Generator is an open-source framework designed to generate high-quality synthetic tabular datasets that replicate the statistical characteristics of real data while avoiding privacy risks. The platform enables developers and data scientists to create artificial datasets that preserve important relationships between variables without containing sensitive personal information. This makes the generated data suitable for tasks such as machine learning model training, testing software systems, sharing datasets across organizations, and conducting research without violating privacy regulations. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    Foundations-of-LLMs

    Foundations-of-LLMs

    A book for Learning the Foundations of LLMs

    ...Developed by researchers at Zhejiang University, it provides structured explanations of both established methods and emerging AI technologies. The material covers statistical language models, recurrent neural networks, Transformers, and modern language model architectures. Dedicated chapters explore prompt engineering, in-context learning, and chain-of-thought reasoning. Readers also learn parameter-efficient fine-tuning, model editing, and retrieval-augmented generation. The repository includes downloadable textbook chapters, an English edition, diagrams, and collections of relevant academic papers. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next