Showing 7 open source projects for "ai coding model"

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    Unity ML-Agents Toolkit

    Unity ML-Agents Toolkit

    Unity machine learning agents toolkit

    ...To create intelligent behaviors, developers have had to resort to writing tons of code or using highly specialized tools. With Unity Machine Learning Agents (ML-Agents), you are no longer “coding” emergent behaviors, but rather teaching intelligent agents to “learn” through a combination of deep reinforcement learning and imitation learning. Using ML-Agents allows developers to create more compelling gameplay and an enhanced game experience. Advancement of artificial intelligence (AI) research depends on figuring out tough problems in existing environments using current benchmarks for training AI models. ...
    Downloads: 0 This Week
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  • 2
    MedicalGPT

    MedicalGPT

    MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training

    MedicalGPT training medical GPT model with ChatGPT training pipeline, implementation of Pretraining, Supervised Finetuning, Reward Modeling and Reinforcement Learning. MedicalGPT trains large medical models, including secondary pre-training, supervised fine-tuning, reward modeling, and reinforcement learning training.
    Downloads: 1 This Week
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  • 3
    H2O LLM Studio

    H2O LLM Studio

    Framework and no-code GUI for fine-tuning LLMs

    Welcome to H2O LLM Studio, a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). You can also use H2O LLM Studio with the command line interface (CLI) and specify the configuration file that contains all the experiment parameters. To finetune using H2O LLM Studio with CLI, activate the pipenv environment by running make shell. With H2O LLM Studio, training your large language model is easy and intuitive. First, upload your dataset and then start...
    Downloads: 4 This Week
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  • 4
    ML for Trading

    ML for Trading

    Code for machine learning for algorithmic trading, 2nd edition

    On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms,...
    Downloads: 2 This Week
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  • 5
    TaskWeaver

    TaskWeaver

    A code-first agent framework for seamlessly planning analytics tasks

    TaskWeaver is a multi-agent AI framework designed for orchestrating autonomous agents that collaborate to complete complex tasks.
    Downloads: 0 This Week
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  • 6
    Hands-on Unsupervised Learning

    Hands-on Unsupervised Learning

    Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)

    This repo contains the code for the O'Reilly Media, Inc. book "Hands-on Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data" by Ankur A. Patel. Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot...
    Downloads: 0 This Week
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  • 7
    TensorLayer

    TensorLayer

    Deep learning and reinforcement learning library for scientists

    ...In the future, it will support TensorFlow, MindSpore, PaddlePaddle, PyTorch and other backends. TensorLayer has a high-level layer/model abstraction which is effortless to learn. You can learn how deep learning can benefit your AI tasks in minutes through the massive examples.
    Downloads: 2 This Week
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