登录
首页 » WINDOWS » 机器学习实战

机器学习实战

于 2017-07-12 发布 文件大小:50358KB
0 306
下载积分: 1 下载次数: 106

代码说明:

  机器学习实战,主要介绍机器学习的内容,使用python作为源代码语言(machine learning in action)

文件列表:

机器学习实战源代码.rar
Machine Learning in Action.pdf
机器学习实战.pdf

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • xinwenxue
    说明:  新闻学的著作,适合想要学习新闻媒体的朋友学习的基础课程电子书。(Journalism books for friends in the media want to learn to learn a basic course books.)
    2010-04-20 13:13:52下载
    积分:1
  • Art_of_writing_testbenches
    Art_of_writing_testbenches,学习写testbench的经典书籍(Art_of_writing_testbenches. Learning to write the classic books testbench)
    2006-08-24 11:33:01下载
    积分:1
  • cgaa.3rd-edn.cn.pdf
    计算机图形学 清华大学出版社 PDF格式(Computer graphics books in PDF format, Tsinghua University Press)
    2013-11-19 10:32:21下载
    积分:1
  • Python
    PYTHON核心教程,PYTHON开发必读(PYTHON core curriculum, PYTHON development of reading)
    2020-06-25 01:40:02下载
    积分:1
  • 外弹道测量数据处理
    外弹道测量数据处理理论书籍pdf,很实用,内容全面对外场试验处理有指导作用(exterior ballistic data processing)
    2021-03-13 15:09:24下载
    积分:1
  • box-girder-beam3
    Ansys 中变截面连续箱梁建模,静力分析,模态分析以及设计弯矩绘制,影响线的绘制等。(Variable cross-section continuous box girder model in Ansys, the static analysis, modal analysis, and design bending moment, influence line drawing, etc.)
    2014-06-10 21:50:39下载
    积分:1
  • diveintopythonzh-cn-5.4b-code
    python工具书查询,之前看到的,资料还不错,可以参考学习下(Reference books for python)
    2020-06-18 07:40:02下载
    积分:1
  • The little SAS book
    说明:  《The Little SAS Book 中文版》以大量实例、清晰简明的解释以及尽可能少的术语来介绍SAS语言,且大部分的功能均来自Base SAS。Base SAS包含了所有程序员所使用的核心功能。(The Little SAS Book Chinese Edition introduces SAS language with a large number of examples, clear and concise explanations and as few terms as possible, and most of its functions come from Base SAS. Base SAS contains the core functions used by all programmers.)
    2020-06-18 03:40:01下载
    积分:1
  • kaggle_diabetic-master
    说明:  A commented bash script to generate our final 2nd place solution can be found in make_kaggle_solution.sh. Running all the commands sequentially will probably take 7 - 10 days on recent consumer grade hardware. If you have multiple GPUs you can speed things up by doing training and feature extraction for the two networks in parallel. However, due to the computationally heavy data augmentation it may be far less than twice as fast especially when working with 512x512 pixel input images. You can also obtain a quadratic weighted kappa score of 0.839 on the private leaderboard by just training the 4x4 kernel networks and by performing only 20 feature extraction iterations with the weights that gave you the best MSE validation scores during training. The entire ensemble only achieves a slightly higher score of 0.845.
    2019-05-11 15:31:21下载
    积分:1
  • 集成运算放大器应用电路集萃
    说明:  一本有效用于学习运算放大器的书籍,通过多种实验图纸给出了详细的工作状况(A book for effective learning of operational amplifiers)
    2019-06-20 14:54:40下载
    积分:1
  • 696516资源总数
  • 106562会员总数
  • 4今日下载