Showing 10 open source projects for "engineer"

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  • 1
    AI Engineer Headquarters

    AI Engineer Headquarters

    A collection of scientific methods, processes, algorithms

    AI-Engineer-Headquarters is a comprehensive educational repository designed to help developers become advanced AI engineers through a structured learning path and practical system-building exercises. The project serves as a curated collection of resources, methodologies, and tools covering topics across the entire artificial intelligence development lifecycle.
    Downloads: 0 This Week
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  • 2
    Karpathy

    Karpathy

    An agentic Machine Learning Engineer

    karpathy is an experimental agentic machine learning engineer framework designed to automate many aspects of the ML development workflow. The project sets up a sandboxed environment where an AI agent can access datasets, run experiments, and generate machine learning artifacts through a web interface. Its startup script automatically prepares the environment by creating a sandbox directory, installing key ML libraries, and launching the agent interface.
    Downloads: 1 This Week
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  • 3
    Advanced Solutions Lab

    Advanced Solutions Lab

    This repos contains notebooks for the Advanced Solutions Lab

    ...This is maintained by Google Cloud’s Advanced Solutions Lab (ASL) team. Vertex AI is the next-generation AI Platform on the Google Cloud Platform. The material covered in this repo will take a software engineer with no exposure to machine learning to an advanced level.
    Downloads: 0 This Week
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  • 4
    Hummingbird

    Hummingbird

    Hummingbird compiles trained ML models into tensor computation

    ...Thanks to Hummingbird, users can benefit from (1) all the current and future optimizations implemented in neural network frameworks; (2) native hardware acceleration; (3) having a unique platform to support both traditional and neural network models; and having all of this (4) without having to re-engineer their models.
    Downloads: 1 This Week
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  • 5
    Machine Learning Systems

    Machine Learning Systems

    Introduction to Machine Learning Systems

    Machine Learning Systems is an open educational repository that serves as the source and learning stack for the Machine Learning Systems textbook, a project focused on teaching how to engineer AI systems that work reliably in real-world environments. Rather than concentrating only on model training, the material emphasizes the broader discipline of AI engineering, covering efficiency, reliability, deployment, and evaluation across the full lifecycle of intelligent systems. The repository includes textbook content, supporting labs, and companion tools such as TinyTorch to help learners move from theory to hands-on experimentation. ...
    Downloads: 3 This Week
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  • 6
    ML Intern

    ML Intern

    ML engineer that reads papers, trains models, and ships ML models

    ML Intern is a repository by Hugging Face that provides educational content and projects aimed at helping learners gain practical experience in machine learning and AI development. It is designed to simulate the experience of working as a machine learning intern, offering tasks and exercises that mirror real-world workflows. The project includes tutorials, datasets, and example implementations that guide users through different aspects of ML development. It emphasizes hands-on learning,...
    Downloads: 0 This Week
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  • 7
    AIGC-Interview-Book

    AIGC-Interview-Book

    AIGC algorithm engineer interview secrets

    AIGC-Interview-Book is a large educational repository designed to help engineers prepare for technical interviews related to artificial intelligence and generative AI roles. The project compiles knowledge from industry practitioners and researchers into a structured reference covering the AI ecosystem. Topics included in the repository span large language models, generative AI systems, traditional deep learning methods, reinforcement learning, computer vision, natural language processing,...
    Downloads: 0 This Week
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  • 8
    Machine Learning for Software Engineers

    Machine Learning for Software Engineers

    A complete daily plan for studying to become a machine learning engine

    Machine Learning for Software Engineers is an open-source learning roadmap designed to help software engineers transition into machine learning roles through a structured, practical study plan. The repository presents a top-down learning path that emphasizes hands-on experience rather than heavy theoretical prerequisites, making it particularly approachable for developers who already have programming experience but limited formal training in machine learning. The project organizes a...
    Downloads: 0 This Week
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  • 9
    Feature-engine

    Feature-engine

    Feature engineering package with sklearn like functionality

    Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow Scikit-learn's functionality with fit() and transform() methods to learn the transforming parameters from the data and then transform it.
    Downloads: 0 This Week
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  • 10
    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: 0 This Week
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