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  • 醉染图书fastai与PyTorch深度学习实践指南()9787564194543
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    • 作者: (美)杰瑞米·霍华德,(法)西尔万·古戈尔著 | (美)杰瑞米·霍华德,(法)西尔万·古戈尔编 | (美)杰瑞米·霍华德,(法)西尔万·古戈尔译 | (美)杰瑞米·霍华德,(法)西尔万·古戈尔绘
    • 出版社: 东南大学出版社
    • 出版时间:2021-04-01
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    新春将至,本公司假期时间为:2025年1月23日至2025年2月7日。2月8日订单陆续发货,期间带来不便,敬请谅解!

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    • 作者: (美)杰瑞米·霍华德,(法)西尔万·古戈尔著| (美)杰瑞米·霍华德,(法)西尔万·古戈尔编| (美)杰瑞米·霍华德,(法)西尔万·古戈尔译| (美)杰瑞米·霍华德,(法)西尔万·古戈尔绘
    • 出版社:东南大学出版社
    • 出版时间:2021-04-01
    • 版次:1
    • 印次:1
    • 字数:759000
    • 页数:588
    • 开本:16开
    • ISBN:9787564194543
    • 版权提供:东南大学出版社
    • 作者:(美)杰瑞米·霍华德,(法)西尔万·古戈尔
    • 著:(美)杰瑞米·霍华德,(法)西尔万·古戈尔
    • 装帧:平装
    • 印次:1
    • 定价:169.00
    • ISBN:9787564194543
    • 出版社:东南大学出版社
    • 开本:16开
    • 印刷时间:暂无
    • 语种:暂无
    • 出版时间:2021-04-01
    • 页数:588
    • 外部编号:1202331554
    • 版次:1
    • 成品尺寸:暂无

    Preface

    Foreword

    Part . eep Learning in Practice

    1. Your Deep Learning Journey

    Deep Learning Is for Everyone

    Neural Networks: A Brief History

    Who We Are

    How to Learn Deep Learning

    Your ProjecsndYur Mindset

    The Software: PyTorch, fastai, and Jupyter (And Why t oesnt Matter)

    Your First Model

    Getting a GPU Deep Learning Server

    Running Your First Notebook

    What Is Machine Learning?

    What Is a Neural Network?

    A Bit of Deep Learning Jargon

    Limitations Inherent to Machine Learning

    How Our Image Recognizer Works

    What Our Image Recognizer Learned

    Image Recognizers Can Tackle Non-Image Tasks

    Jargon Recap

    Deep Learning Is Not Just for Image Classification

    Validation Sets and Test Sets

    Use Judgment in Defining Test Sets

    A Choose Your Own Adventure Moment

    estionnaire

    Further Research

    2. From Model to Production

    The Practice of Deep Learning

    Starting Your Project

    The State of Deep Learning

    The Drivetrain Approach

    Gathering Data

    From Data to DataLoaders

    Data Augmentation

    Training Your Model, and Using It to Clean Your Data

    Turning Your Model into an Online Application

    Using the Model for Inference

    Creating a Notebook App from the Model

    Turning Your Notebook into a Real App

    Deploying Your App

    How to Avoid Disaster

    Unforeseen Consequences and Feedback Loops

    Get Writing!

    estionnaire

    Further Research

    3. Data Ethics

    Key Examples for Data Ethics

    Bugs and Recourse: Buggy Algorithm Used for Healthcare Benefits

    Feedback Loops: YouTubes Recommendation System

    Bias: Professor Latanya Sweeney "Arrested"

    Why Does This Matter?

    Integrating Machine Learning with Product Design

    Topics in Data Ethics

    Recourse and Accountability

    Feedback Loops

    Bias

    Disinformation

    Identifying and Addressing Ethical Issues

    Analyze a Project You Are Working On

    Processes to Implement

    The Power of Diversity

    ……

    Part II. Understanding fastais applications

    Part III. Foundations of Deep Learning

    Part IV. Deep learning from Scratch

    Index

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