Keras: 基于 Python 的深度学习库Model 对象. 参考文献 • Xception: Deep Learning with Depthwise Separable Convolutions License 预训练权值由我们自己训练而来,基于 MIT license 发布。 13.3.2 VGG16 keras.applications.vgg16.VGG16(include_top=True, weights='imagenet' for Large-Scale Image Recognition:如果在研究中使用了 VGG,请引用该论文。 License 预训练权值由 VGG at Oxford 发布的预训练权值移植而来,基于 Creative Commons Attribu- tion License。 13.3.3 VGG19 keras.applications.vgg19.VGG19(include_top=True for Large-Scale Image Recognition:如果在研究中使用了 VGG,请引用该论文。 License 预训练权值由 VGG at Oxford 发布的预训练权值移植而来,基于 Creative Commons Attribu- tion License。 预训练模型 APPLICATIONS 165 13.3.4 ResNet50 keras.applications0 码力 | 257 页 | 1.19 MB | 1 年前3
QCon北京2018-《从键盘输入到神经网络--深度学习在彭博的应用》-李碧野Modified from https://upload.wikimedia.org/wikipedia/commons/d/dc/UnderwoodKeyboard_%28transparent%29.png https://upload.wikimedia.org/wikipedia/commons/1/18/1328102022_Document.png May be re-distributed re-distributed in accordance with the terms of the CC-SA 4.0 license https://creativecommons.org/licenses/by-sa/4.0/deed.en AAPL FB 700 GOOG TXT BIDU ? ? ? ? © 2018 Bloomberg Finance L.P. All rights reserved https://commons.wikimedia.org/wiki/Category:Machine_learning_algorithms#/media/File:Moving_From_unknown_to_known_feature_spaces_based_on_TS-ELM_with_random_kernels_and_connections.tif https://commons.wikimedia0 码力 | 64 页 | 13.45 MB | 1 年前3
AI大模型千问 qwen 中文文档Modelfile 的文件。该文件的内容如下所示: FROM qwen1_5-7b-chat-q4_0.gguf # set the temperature to 1 [higher is more creative, lower is more coherent] PARAMETER temperature 0.7 PARAMETER top_p 0.8 PARAMETER repeat_penalty0 码力 | 56 页 | 835.78 KB | 1 年前3
《Efficient Deep Learning Book》[EDL] Chapter 3 - Learning Techniquesunder CC BY-SA 3.0 license. They are authored by wikipedia users Joaquim Alves Gaspar and Losch respectively. The pigeon and parrot images are sourced under Pexels Free To Use license. They are authored0 码力 | 56 页 | 18.93 MB | 1 年前3
PyTorch Release NotesNVIDIA product in any manner that is contrary to this document or (ii) customer product designs. No license, either expressed or implied, is granted under any NVIDIA patent right, copyright, or other NVIDIA or services does not constitute a license from NVIDIA to use such products or services or a warranty or endorsement thereof. Use of such information may require a license from a third party under the patents patents or other intellectual property rights of the third party, or a license from NVIDIA under the patents or other intellectual property rights of NVIDIA. Reproduction of information in this document0 码力 | 365 页 | 2.94 MB | 1 年前3
【PyTorch深度学习-龙龙老师】-测试版202112,将其展开为标量形式: ?(?) = ?1?1 + ?2?2 + ?3?3 + ⋯ + ???? + ? 上述计算逻辑可以通过图 2.2(b)直观地展现。 ① 素材来自 https://commons.wikimedia.org/wiki/File:Neuron_Hand-tuned.svg 预览版202112 第 2 章 回归问题 2 ?1 ?2 ?30 码力 | 439 页 | 29.91 MB | 1 年前3
《Efficient Deep Learning Book》[EDL] Chapter 7 - Automationindicate poor results. The 'x' marks indicate the trials. The images are sourced under CC BY-SA 4.0 license from Hyperparameter optimization article on wikipedia. Grid Search has serious limitations for real0 码力 | 33 页 | 2.48 MB | 1 年前3
keras tutorial28 2018, 17:00:18) [MSC v.1900 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> As of now the latest version is ‘3.7.2’. If Python is not installed0 码力 | 98 页 | 1.57 MB | 1 年前3
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