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1722332572
V2EX  ›  Python

调参侠的末日? Auto-Keras 自动搜索深度学习模型的网络架构和超参数

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  •   1722332572 · Aug 3, 2018 · 9259 views
    This topic created in 3014 days ago, the information mentioned may be changed or developed.
    Auto-Keras 是一个开源的自动机器学习库。Auto-Keras 的终极目标是允许所有领域的只需要很少的数据科学或者机器学习背景的专家都可以很容易的使用深度学习。Auto-Keras 提供了一系列函数来自动搜索深度学习模型的网络和超参数。

    安装:

    pip install autokeras

    样例:

    import autokeras as ak
    clf = ak.ImageClassifier()
    clf.fit(x_train, y_train)
    results = clf.predict(x_test)

    官方网站: http://autokeras.com/
    开源项目: https://github.com/jhfjhfj1/autokeras

    Auto-Keras is an open source software library for automated machine learning (AutoML). The ultimate goal of AutoML is to allow domain experts with limited data science or machine learning background easily accessible to deep learning models. Auto-Keras provides functions to automatically search for architecture and hyperparameters of deep learning models.

    翻译: http://www.tf86.com/2018/08/03/auto-keras/
    13 replies  •  2018-08-08 15:12:59 +08:00
    bwael
    bwael
    Aug 3, 2018
    1
    抢个沙发试试。auto-keras,有点可怕。
    geekcorn
    geekcorn
    Aug 3, 2018 via iPhone
    2
    哇&&&)
    sangleft
    sangleft
    Aug 3, 2018 via Android
    3
    等会就试试…😯
    ddzzhen
    ddzzhen
    Aug 3, 2018 via Android
    4
    看起来有点牛批,sklearn 的翻版?
    xxxy
    xxxy
    Aug 3, 2018❤️1
    5
    sklearn 不是有个 gridSearch?跟那个有什么区别?
    owenliang
    owenliang
    Aug 3, 2018 via Android
    6
    深度学习帮码农挑选优质特征
    thedog
    thedog
    Aug 3, 2018 via Android
    7
    @xxxy 神经网络超参数太多,不会用网格搜索这种遍历调参的。调参的时候蛮多 trick 的
    OLDPAN
    OLDPAN
    Aug 3, 2018
    8
    之前是自动调参数,现在是自动调网络
    1722332572
    1722332572
    OP
    Aug 3, 2018
    9
    @xxxy 看文档,这个模型也会调。
    takato
    takato
    Aug 3, 2018
    10
    本质是个 NAS 吧。
    eastrd
    eastrd
    Aug 4, 2018 via Android
    11
    不是已经有 hpot 了吗?
    northisland
    northisland
    Aug 4, 2018
    12
    厉害了!
    虽然 tensorflow 很难用,但为了这些周边,还是值得搞 TF 的~

    First, each dataset is split by60-20-20 into training, validation and testing set.
    Second, **run the method for 12 hours** on a single GPU (NVIDIA GeForce GTX 1080Ti) on the training and validation set.
    Third, the output architecture is trained with both training and validation set.
    Fourth, the testing set is used to evaluate the trained architecture

    最近经常见 200 块 gpu,训练个把月的 RL 文章,这方法简直是一股清流
    1722332572
    1722332572
    OP
    Aug 8, 2018
    13
    @northisland 调参侠的福音,还顺便调网络结构,美滋滋。
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