首页 磁力链接怎么用

[Lynda] Applied Machine Learning - Foundations

文件类型 收录时间 最后活跃 资源热度 文件大小 文件数量
视频 2020-1-10 23:35 2024-10-29 06:48 129 377.31 MB 36
磁力链接
magnet:?xt=urn:btih:618897021fba0eea000f38e4eb533bddb087a150
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjYxODg5NzAyMWZiYTBlZWEwMDBmMzhlNGViNTMzYmRkYjA4N2ExNTBaWg==
二维码链接
[Lynda] Applied Machine Learning - Foundations的二维码
种子下载(838888不存储任何种子文件)
种子下载线路1(迅雷)--推荐
种子下载线路2(比特彗星)
种子下载线路3(torcache)
3条线路均为国内外知名下载网站种子链接，内容跟本站无关！
相关链接

Lynda Applied Machine Learning - Foundations

文件列表
  1. [Lynda] Applied Machine Learning - Foundations/1.Introduction/01.Leveraging machine learning.mp419.14MB
  2. [Lynda] Applied Machine Learning - Foundations/1.Introduction/02.What you should know.mp44.49MB
  3. [Lynda] Applied Machine Learning - Foundations/1.Introduction/03.What tools you need.mp41.62MB
  4. [Lynda] Applied Machine Learning - Foundations/1.Introduction/04.Using the exercise files.mp43.06MB
  5. [Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/05.What is machine learning.mp45.98MB
  6. [Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/06.What kind of problems can this help you solve.mp48.31MB
  7. [Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/07.Why Python.mp412.14MB
  8. [Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/08.Machine learning vs. Deep learning vs. Artificial intelligence.mp46.87MB
  9. [Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/09.Demos of machine learning in real life.mp410.55MB
  10. [Lynda] Applied Machine Learning - Foundations/2.1. Machine Learning Basics/10.Common challenges.mp48.98MB
  11. [Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/11.Why do we need to explore and clean our data.mp45.2MB
  12. [Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/12.Exploring continuous features.mp424.23MB
  13. [Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/13.Plotting continuous features.mp417.86MB
  14. [Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/14.Continuous data cleaning.mp415.07MB
  15. [Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/15.Exploring categorical features.mp415.14MB
  16. [Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/16.Plotting categorical features.mp414.29MB
  17. [Lynda] Applied Machine Learning - Foundations/3.2. Exploratory Data Analysis and Data Cleaning/17.Categorical data cleaning.mp411.02MB
  18. [Lynda] Applied Machine Learning - Foundations/4.3. Measuring Success/18.Why do we split up our data.mp49.49MB
  19. [Lynda] Applied Machine Learning - Foundations/4.3. Measuring Success/19.Split data for train_validation_test set.mp412.99MB
  20. [Lynda] Applied Machine Learning - Foundations/4.3. Measuring Success/20.What is cross-validation.mp49.04MB
  21. [Lynda] Applied Machine Learning - Foundations/4.3. Measuring Success/21.Establish an evaluation framework.mp46.98MB
  22. [Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/22.Bias_Variance tradeoff.mp48.11MB
  23. [Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/23.What is underfitting.mp44.04MB
  24. [Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/24.What is overfitting.mp44.61MB
  25. [Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/25.Finding the optimal tradeoff.mp45.45MB
  26. [Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/26.Hyperparameter tuning.mp49.63MB
  27. [Lynda] Applied Machine Learning - Foundations/5.4. Optimizing a Model/27.Regularization.mp44.41MB
  28. [Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/28.Overview of the process.mp42.57MB
  29. [Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/29.Clean continuous features.mp413.79MB
  30. [Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/30.Clean categorical features.mp410.62MB
  31. [Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/31.Split data into train_validation_test set.mp49.71MB
  32. [Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/32.Fit a basic model using cross-validation.mp414.91MB
  33. [Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/33.Tune hyperparameters.mp418.15MB
  34. [Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/34.Evaluate results on validation set.mp418.55MB
  35. [Lynda] Applied Machine Learning - Foundations/6.5. End-to-End Pipeline/35.Final model selection and evaluation on test set.mp424.12MB
  36. [Lynda] Applied Machine Learning - Foundations/7.Conclusion/36.Next steps.mp46.19MB
友情提示
不会用的朋友看这里 把磁力链接复制到离线下载，或者bt下载软件里即可下载文件，或者直接复制迅雷链接到迅雷里下载！ 亲，你造吗？将网页分享给您的基友，下载的人越多速度越快哦！

违规内容投诉邮箱：[email protected]

概述 838888磁力搜索是一个磁力链接搜索引擎，是学术研究的副产品，用于解决资源过度分散的问题 它通过BitTorrent协议加入DHT网络，实时的自动采集数据，仅存储文件的标题、大小、文件列表、文件标识符（磁力链接）等基础信息 838888磁力搜索不下载任何真实资源，无法判断资源的合法性及真实性，使用838888磁力搜索服务的用户需自行鉴别内容的真伪 838888磁力搜索不上传任何资源，不提供Tracker服务，不提供种子文件的下载，这意味着838888磁力搜索 838888磁力搜索是一个完全合法的系统
838888磁力链接 磁力链接bt种子搜索引擎磁力搜索 DMCA