[CourseClub.NET] Coursera - Applied Machine Learning in Python

磁力链接/BT种子名称

[CourseClub.NET] Coursera - Applied Machine Learning in Python

磁力链接/BT种子简介

种子哈希：2aebbd9a938b03ea4de16737994cb85b9fbdfd68
文件大小：881.06M
已经下载：4201次
下载速度：极快
收录时间：2020-01-24
最近下载：2025-10-09

地址随时变，回家记住路

小野猫.com黑猫警长.com哆啦a猫.com御猫.com科目三.com猫哭老鼠.com女猫.com☜☜☜找最新地址请保存左面网址

磁力链接

magnet:?xt=urn:btih:2AEBBD9A938B03EA4DE16737994CB85B9FBDFD68
推荐使用PIKPAK网盘下载资源，PIKPAK是目前最好用网盘，10T超大空间，不和谐任何资源，支持无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 在线观看 世界之窗 含羞草 极乐禁地 91视频 51品茶 逼哩逼哩 萝莉岛 欲漫涩 91短视频 成人快手 抖阴破解版 ai色色 pilipili 草榴社区 哆哔涩漫 好色先生 疯马秀 TikTok成人版 悠悠禁区 波多 听泉鉴鲍 xvideo 外网天堂 PornHub 抖音Max 呦乐园 拔萝卜 糖心视频 麻豆Vlog 暗网Xvideo

资源截图

API Integration

最近搜索

文件列表

  • 003.Module 3 Evaluation/019. Model Evaluation & Selection.mp4 48.3 MB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/002. Key Concepts in Machine Learning.mp4 46.7 MB
  • 004.Module 4 Supervised Machine Learning - Part 2/029. Neural Networks.mp4 43.5 MB
  • 002.Module 2 Supervised Machine Learning/012. Linear Regression Ridge, Lasso, and Polynomial Regression.mp4 41.9 MB
  • 002.Module 2 Supervised Machine Learning/016. Kernelized Support Vector Machines.mp4 41.0 MB
  • 002.Module 2 Supervised Machine Learning/007. Introduction to Supervised Machine Learning.mp4 39.7 MB
  • 002.Module 2 Supervised Machine Learning/018. Decision Trees.mp4 39.7 MB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/006. K-Nearest Neighbors Classification.mp4 38.0 MB
  • 003.Module 3 Evaluation/025. Model Selection Optimizing Classifiers for Different Evaluation Metrics.mp4 36.2 MB
  • 004.Module 4 Supervised Machine Learning - Part 2/031. Data Leakage.mp4 34.5 MB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/005. Examining the Data.mp4 33.8 MB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/004. An Example Machine Learning Problem.mp4 33.3 MB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/001. Introduction.mp4 32.6 MB
  • 002.Module 2 Supervised Machine Learning/011. Linear Regression Least-Squares.mp4 31.5 MB
  • 005.Optional Unsupervised Machine Learning/034. Clustering.mp4 28.5 MB
  • 004.Module 4 Supervised Machine Learning - Part 2/027. Random Forests.mp4 27.7 MB
  • 002.Module 2 Supervised Machine Learning/014. Linear Classifiers Support Vector Machines.mp4 23.8 MB
  • 002.Module 2 Supervised Machine Learning/010. K-Nearest Neighbors Classification and Regression.mp4 23.6 MB
  • 004.Module 4 Supervised Machine Learning - Part 2/026. Naive Bayes Classifiers.mp4 22.4 MB
  • 003.Module 3 Evaluation/020. Confusion Matrices & Basic Evaluation Metrics.mp4 21.8 MB
  • 002.Module 2 Supervised Machine Learning/013. Logistic Regression.mp4 21.3 MB
  • 002.Module 2 Supervised Machine Learning/017. Cross-Validation.mp4 21.0 MB
  • 003.Module 3 Evaluation/023. Multi-Class Evaluation.mp4 20.7 MB
  • 002.Module 2 Supervised Machine Learning/008. Overfitting and Underfitting.mp4 20.5 MB
  • 004.Module 4 Supervised Machine Learning - Part 2/030. Deep Learning (Optional).mp4 18.3 MB
  • 003.Module 3 Evaluation/024. Regression Evaluation.mp4 17.8 MB
  • 005.Optional Unsupervised Machine Learning/033. Dimensionality Reduction and Manifold Learning.mp4 16.9 MB
  • 002.Module 2 Supervised Machine Learning/015. Multi-Class Classification.mp4 16.2 MB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/003. Python Tools for Machine Learning.mp4 13.5 MB
  • 003.Module 3 Evaluation/021. Classifier Decision Functions.mp4 13.3 MB
  • 004.Module 4 Supervised Machine Learning - Part 2/028. Gradient Boosted Decision Trees.mp4 12.4 MB
  • 002.Module 2 Supervised Machine Learning/009. Supervised Learning Datasets.mp4 11.8 MB
  • 005.Optional Unsupervised Machine Learning/032. Introduction.mp4 11.2 MB
  • 006.Conclusion/035. Conclusion.mp4 10.4 MB
  • 003.Module 3 Evaluation/022. Precision-recall and ROC curves.mp4 9.7 MB
  • 003.Module 3 Evaluation/019. Model Evaluation & Selection.srt 30.8 kB
  • 002.Module 2 Supervised Machine Learning/018. Decision Trees.srt 29.0 kB
  • 004.Module 4 Supervised Machine Learning - Part 2/029. Neural Networks.srt 28.6 kB
  • 002.Module 2 Supervised Machine Learning/012. Linear Regression Ridge, Lasso, and Polynomial Regression.srt 27.8 kB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/006. K-Nearest Neighbors Classification.srt 26.8 kB
  • 002.Module 2 Supervised Machine Learning/016. Kernelized Support Vector Machines.srt 26.2 kB
  • 002.Module 2 Supervised Machine Learning/007. Introduction to Supervised Machine Learning.srt 22.7 kB
  • 002.Module 2 Supervised Machine Learning/011. Linear Regression Least-Squares.srt 21.8 kB
  • 005.Optional Unsupervised Machine Learning/034. Clustering.srt 20.4 kB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/002. Key Concepts in Machine Learning.srt 19.3 kB
  • 003.Module 3 Evaluation/025. Model Selection Optimizing Classifiers for Different Evaluation Metrics.srt 18.6 kB
  • 002.Module 2 Supervised Machine Learning/013. Logistic Regression.srt 17.5 kB
  • 002.Module 2 Supervised Machine Learning/010. K-Nearest Neighbors Classification and Regression.srt 17.5 kB
  • 004.Module 4 Supervised Machine Learning - Part 2/027. Random Forests.srt 17.5 kB
  • 004.Module 4 Supervised Machine Learning - Part 2/031. Data Leakage.srt 17.1 kB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/001. Introduction.srt 16.5 kB
  • 003.Module 3 Evaluation/020. Confusion Matrices & Basic Evaluation Metrics.srt 16.2 kB
  • 002.Module 2 Supervised Machine Learning/008. Overfitting and Underfitting.srt 16.2 kB
  • 002.Module 2 Supervised Machine Learning/014. Linear Classifiers Support Vector Machines.srt 15.9 kB
  • 003.Module 3 Evaluation/023. Multi-Class Evaluation.srt 15.6 kB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/004. An Example Machine Learning Problem.srt 15.2 kB
  • 005.Optional Unsupervised Machine Learning/033. Dimensionality Reduction and Manifold Learning.srt 13.8 kB
  • 002.Module 2 Supervised Machine Learning/017. Cross-Validation.srt 13.3 kB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/005. Examining the Data.srt 12.3 kB
  • 004.Module 4 Supervised Machine Learning - Part 2/026. Naive Bayes Classifiers.srt 11.5 kB
  • 004.Module 4 Supervised Machine Learning - Part 2/030. Deep Learning (Optional).srt 10.6 kB
  • 003.Module 3 Evaluation/021. Classifier Decision Functions.srt 9.3 kB
  • 004.Module 4 Supervised Machine Learning - Part 2/028. Gradient Boosted Decision Trees.srt 8.6 kB
  • 002.Module 2 Supervised Machine Learning/015. Multi-Class Classification.srt 8.5 kB
  • 003.Module 3 Evaluation/024. Regression Evaluation.srt 8.0 kB
  • 003.Module 3 Evaluation/022. Precision-recall and ROC curves.srt 7.7 kB
  • 002.Module 2 Supervised Machine Learning/009. Supervised Learning Datasets.srt 6.9 kB
  • 005.Optional Unsupervised Machine Learning/032. Introduction.srt 6.6 kB
  • 001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/003. Python Tools for Machine Learning.srt 6.3 kB
  • 006.Conclusion/035. Conclusion.srt 4.0 kB
  • [CourseClub.NET].url 123 Bytes
  • [FreeCourseSite.Com].url 53 Bytes
  • [DesireCourse.Com].url 51 Bytes

温馨提示

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！