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w7_gaussianProcesses
machine learning 方面有关于Bayesian Review and Gaussian Processes的资料，语言是python(machine learning aspects of information concerning the Bayesian Review and Gaussian Processes, language is python)
- 2013-12-07 23:22:26下载
- 积分：1
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login126
python实现126邮箱自动登录源码，需要一些类库支持才能运行，请先下载相关类库.(python achieve 126 mailboxes automatically log source, need some support in order to run the library, please download library.)
- 2014-05-25 23:03:28下载
- 积分：1
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Python 自定义FTP功能 实例源码
Python 自定义FTP功能 实例源码
- 2015-02-11下载
- 积分：1
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matlab手写卷积神经网络人脸识别
基于卷积神经网络的人脸识别，学生作品啊啊啊啊啊啊(open face cnn student school what i should do)
- 2021-04-20 16:48:50下载
- 积分：1
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kmeans
最简单易懂的聚类方法，用python实现k-means对数据的聚类(The most straightforward clustering method, using python to achieve k-means clustering of data)
- 2020-12-22 21:19:06下载
- 积分：1
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5.Python程序中P-中值问题的模拟退火。
1；
- 2022-10-30 01:30:04下载
- 积分：1
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REST-API-SENSOR
说明： Simple code to create a Restful API with flask.
- 2021-01-19 10:28:42下载
- 积分：1
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MIKE11 data_input converter
可以提取CAD中点的坐标信息并转为MIKE地理信息数据输入格式(The coordinate information of midpoint in CAD can be extracted and converted to MIKE geographic information data input format.)
- 2020-06-24 09:20:01下载
- 积分：1
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dlbook_cn_v0.5-beta
(中文版)深度学习(Deep Learning)是由Yoshua Bengio推出的机器学习领域的教科书，以开源的形式免费在网络上提供，主要面向学习机器学习的学生和研究者，以及没有机器学习背景但希望能快速地掌握这方面知识并在他们的产品中使用的软件工程师。(Deep Learning by Yoshua Bengio launched a textbook in the field of machine Learning, in the form of open source provided for free on the Internet, mainly for Learning machine Learning of students and researchers, and the lack of machine Learning background but hope to be able to quickly grasp the knowledge and use of software engineer in their products.)
- 2020-06-20 11:20:02下载
- 积分：1
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机器学习实战 = Machine Learning in Action
说明： 机器学习是人工智能研究领域中的一个极其重要的方向。在现今大数据时代的背景下，捕获数据并从中萃取有价值的信息或模式，使得这一过去为分析师与数学家所专属的研究领域越来越为人们瞩目。本书通过精心编排的实例，切入日常工作任务，摒弃学术化语言，利用高效可复用的Python 代码阐释如何处理统计数据，进行数据分析及可视化。读者可从中学到一些核心的机器学习算法，并将其运用于某些策略性任务中，如分类、预测及推荐等。(Machine learning is an extremely important direction in the field of artificial intelligence research. In the context of the current era of big data, capturing data and extracting valuable information or patterns from it has made this research area that was exclusive to analysts and mathematicians more and more attractive. Through well-organized examples, this book cuts into daily work tasks, abandons academic languages, and uses efficient and reusable Python code to explain how to process statistical data, perform data analysis and visualization. Readers can learn some core machine learning algorithms and apply them to certain strategic tasks, such as classification, prediction, and recommendation.)
- 2019-12-06 15:25:55下载
- 积分：1
