首页 磁力链接怎么用

Building Machine Learning Models in Spark 2

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 2018-8-4 05:52 2024-8-21 00:13 47 397.87 MB 54
磁力链接
magnet:?xt=urn:btih:a6a4e83e38b99033b196dbce5a7a4e84172ede98
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOmE2YTRlODNlMzhiOTkwMzNiMTk2ZGJjZTVhN2E0ZTg0MTcyZWRlOThaWg==
二维码链接
Building Machine Learning Models in Spark 2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

Building Machine Learning Models in Spark 2

文件列表
  1. 01.Course Overview/0101.Course Overview.mp44.89MB
  2. 02.Machine Learning Packages spark.mllib vs. spark.ml/0201.Module Overview.mp42.59MB
  3. 02.Machine Learning Packages spark.mllib vs. spark.ml/0202.Prerequisites and Course Overview.mp44.55MB
  4. 02.Machine Learning Packages spark.mllib vs. spark.ml/0203.RDDs The Building Blocks of Spark.mp45.63MB
  5. 02.Machine Learning Packages spark.mllib vs. spark.ml/0204.DataFrames in Spark 2.mp42.62MB
  6. 02.Machine Learning Packages spark.mllib vs. spark.ml/0205.Demo Spark 2 Installation and Working with Jupyter Notebooks.mp49.19MB
  7. 02.Machine Learning Packages spark.mllib vs. spark.ml/0206.spark.mllib vs. spark.ml.mp46.5MB
  8. 02.Machine Learning Packages spark.mllib vs. spark.ml/0207.Introducing Decision Trees.mp47.43MB
  9. 02.Machine Learning Packages spark.mllib vs. spark.ml/0208.Gini Impurity and Pros and Cons of Decision Trees.mp48.45MB
  10. 02.Machine Learning Packages spark.mllib vs. spark.ml/0209.Demo Basic Project Setup.mp45.23MB
  11. 02.Machine Learning Packages spark.mllib vs. spark.ml/0210.Demo Wine Classification Using Decision Trees in spark.mllib.mp419.99MB
  12. 02.Machine Learning Packages spark.mllib vs. spark.ml/0211.Demo Working with the LIBSVM Data Format.mp42.68MB
  13. 02.Machine Learning Packages spark.mllib vs. spark.ml/0212.Demo Decision Trees Using the LIBSVM Data Format.mp415.21MB
  14. 03.Building Classification and Regression Models in Spark ML/0301.Module Overview.mp42.46MB
  15. 03.Building Classification and Regression Models in Spark ML/0302.ML Pipelines, Estimators, and Transformers.mp48.69MB
  16. 03.Building Classification and Regression Models in Spark ML/0303.Training and Prediction Pipeline Stages.mp44.83MB
  17. 03.Building Classification and Regression Models in Spark ML/0304.Feature Engineering.mp43.24MB
  18. 03.Building Classification and Regression Models in Spark ML/0305.Feature Extractors.mp45.8MB
  19. 03.Building Classification and Regression Models in Spark ML/0306.Feature Transformers.mp44.91MB
  20. 03.Building Classification and Regression Models in Spark ML/0307.Feature Selectors and Locality Sensitive Hashing.mp41.15MB
  21. 03.Building Classification and Regression Models in Spark ML/0308.The Confusion Matrix Accuracy, Precision, Recall, F1 Score.mp47.42MB
  22. 03.Building Classification and Regression Models in Spark ML/0309.Demo Wine Classification Using Decision Trees in Spark ML.mp47.49MB
  23. 03.Building Classification and Regression Models in Spark ML/0310.Demo Converting Categorical Data to Numeric Values.mp44.72MB
  24. 03.Building Classification and Regression Models in Spark ML/0311.Demo The Decision Tree Classifier.mp46.13MB
  25. 03.Building Classification and Regression Models in Spark ML/0312.Random Forests.mp45.01MB
  26. 03.Building Classification and Regression Models in Spark ML/0313.Demo Income Classification Using Random Forests.mp410.7MB
  27. 03.Building Classification and Regression Models in Spark ML/0314.Demo Using ML Pipelines.mp415.45MB
  28. 03.Building Classification and Regression Models in Spark ML/0315.Demo Predictions Using the Random Forest .mp44.93MB
  29. 03.Building Classification and Regression Models in Spark ML/0316.Introducing Regularized Regression Models to Prevent Overfitting.mp47.43MB
  30. 03.Building Classification and Regression Models in Spark ML/0317.Lasso and Ridge Regression.mp44.01MB
  31. 03.Building Classification and Regression Models in Spark ML/0318.Demo Linear Regression with the Elastic Net Param.mp48.97MB
  32. 03.Building Classification and Regression Models in Spark ML/0319.Demo Predictions Using the Regression Model.mp47.06MB
  33. 03.Building Classification and Regression Models in Spark ML/0320.Demo Hyperparameter Tuning.mp48.72MB
  34. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0401.Module Overview.mp42.88MB
  35. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0402.Supervised and Unsupervised Learning Techniques.mp48.3MB
  36. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0403.Clustering Objectives.mp45.97MB
  37. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0404.Visualizing K-means Clustering.mp43.01MB
  38. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0405.Number of Clusters as a Hyperparameter The Elbow and Silhouette Method.mp410.22MB
  39. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0406.Demo K-means Clustering on the Titanic Dataset.mp413.56MB
  40. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0407.Demo Exploring Clusters.mp418.5MB
  41. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0408.Principal Component Analysis Intuition.mp46.84MB
  42. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0409.Demo Regression Model Without PCA.mp415.32MB
  43. 04.Implementing Clustering and Dimensionality Reduction in Spark ML/0410.Demo Performing Regression on Principal Components.mp414.97MB
  44. 05.Building Recommendation Systems in Spark ML/0501.Module Overview.mp41.79MB
  45. 05.Building Recommendation Systems in Spark ML/0502.Content-based and Collaborative Filtering.mp48MB
  46. 05.Building Recommendation Systems in Spark ML/0503.Estimating the Ratings Matrix.mp410.41MB
  47. 05.Building Recommendation Systems in Spark ML/0504.The Alternating Least Squares Method.mp42.69MB
  48. 05.Building Recommendation Systems in Spark ML/0505.Explicit and Implicit Ratings.mp49.32MB
  49. 05.Building Recommendation Systems in Spark ML/0506.Cold Start Strategies and Compute Intensity.mp42.67MB
  50. 05.Building Recommendation Systems in Spark ML/0507.Demo Building a Recommendation System Using Explicit Ratings.mp48.35MB
  51. 05.Building Recommendation Systems in Spark ML/0508.Demo Getting Movie Recommendations for Specific Users.mp410.86MB
  52. 05.Building Recommendation Systems in Spark ML/0509.Demo Building a Recommendation System Using Implicit Ratings.mp48.53MB
  53. 05.Building Recommendation Systems in Spark ML/0510.Demo Getting Artist Recommendations for Specific Users.mp48.66MB
  54. 05.Building Recommendation Systems in Spark ML/0511.Summary and Further Study.mp42.94MB
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