机器学习课程-温州大学-04机器学习-朴素贝叶斯文本 标签 A great game Sports The election was over Not Sports Very clean match Sports A clean but forgettable game Sports It was a close election Not Sports 我们想要计算句子“A very close game”是 Sports 的概率以及它不 close game )这个句子的类别是Sports的概率 20 3.朴素贝叶斯案例 特征:单词的频率 已知贝叶斯定理?(?|?) = ?(?|?)?(?) ?(?) ,则: ?( Sports | a very close game ) = ?( a very close game | Sports ) × ?( Sports ) ?( a very close game ) 由 数,只是比较 ?( a very close game | Sports ) × ?( Sports ) 和 ?( a very close game | Not Sports ) × ?( Not Sports ) 21 3.朴素贝叶斯案例 我们假设一个句子中的每个单词都与其他单词无关。 ) ?( a very close game ) = ?(?) × ?( very ) × ?(0 码力 | 31 页 | 1.13 MB | 1 年前3
《Efficient Deep Learning Book》[EDL] Chapter 7 - Automationone (the best) configuration left. An intuitive way to think about it is to imagine a multiplayer game with multiple levels where a few best performing players are promoted to the next level until we have on the target dataset. The controller model learns to generate better architectures as the search game progresses. Figure 7-4: An overview of Neural Architecture Search framed as a Reinforcement Learning0 码力 | 33 页 | 2.48 MB | 1 年前3
《Efficient Deep Learning Book》[EDL] Chapter 4 - Efficient Architecturesthe winning goal in the final moments of the game”, we can instantly classify it as a sports article. We recognize that the words scored, winning, goal and game occur together in sports category with high0 码力 | 53 页 | 3.92 MB | 1 年前3
Lecture 1: Overviewfeedback which is not direct I/O pairs for a useful target function. Potentially arbitrary sequences of game moves and their final results Credit/Blame Assignment Problem: How to assign credit blame to individual0 码力 | 57 页 | 2.41 MB | 1 年前3
【PyTorch深度学习-龙龙老师】-测试版202112Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel 和 D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature, 卷 529, pp. 484-503, 2016. [3] D. Silver Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. Driessche, T. Graepel 和 D. Hassabis, “Mastering the game of Go without human knowledge,” Nature, 卷 550, pp. 354--, 10 2017. [4] R. J. Williams, “Simple0 码力 | 439 页 | 29.91 MB | 1 年前3
PyTorch TutorialJupyter Notebook VS Code • Install the Python extension. • ???????????? Install the Remote Development extension. • Python files can be run like Jupyter notebooks by delimiting cells/sections with0 码力 | 38 页 | 4.09 MB | 1 年前3
《TensorFlow 快速入门与实战》6-实战TensorFlow验证码识别模型 训练 参数 调优 模型 部署 识别 服务 使用 Flask 快速搭建 验证码识别服务 使用 Flask 启动 验证码识别服务 $ export FLASK_ENV=development && flask run --host=0.0.0.0 打开浏览器访问测试 URL(http://localhost:5000/ping) 访问 验证码识别服务 $ curl -X POST0 码力 | 51 页 | 2.73 MB | 1 年前3
动手学深度学习 v2.0A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., ⋯ others. (2016). Mastering the game of go with deep neural networks and tree search. nature, 529(7587), 484. [Simonyan & Zisserman,0 码力 | 797 页 | 29.45 MB | 1 年前3
keras tutorialbegin by understanding the model evaluation. Model Evaluation Evaluation is a process during development of the model to check whether the model is best fit for the given problem and corresponding data0 码力 | 98 页 | 1.57 MB | 1 年前3
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