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Lynda - AWS Machine Learning by Example

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视频 2018-11-7 08:55 2024-11-19 23:18 98 210.14 MB 32
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文件列表
  1. 1.Introduction/01.Welcome.mp44.44MB
  2. 1.Introduction/02.What you should know before watching this course.mp43.52MB
  3. 1.Introduction/03.Setting up an AWS account.mp44.8MB
  4. 2.1. Introduction to Machine Learning/04.Machine learning overview.mp42.44MB
  5. 2.1. Introduction to Machine Learning/05.Learning algorithms and hyperparameters.mp47.3MB
  6. 2.1. Introduction to Machine Learning/06.Steps in AWS machine learning.mp42.4MB
  7. 4.2. Binary Model/07.Exploring our binary model data set.mp45.65MB
  8. 4.2. Binary Model/08.Preparing our data for AWS.mp416.58MB
  9. 4.2. Binary Model/09.Creating a datasource.mp45.36MB
  10. 4.2. Binary Model/10.Confirming AWS machine learning schema.mp413.53MB
  11. 4.2. Binary Model/11.Creating a binary classification model.mp44.73MB
  12. 4.2. Binary Model/12.Understanding binary model's predictive performance.mp48.13MB
  13. 4.2. Binary Model/13.Setting binary model's predictive performance.mp47.38MB
  14. 4.2. Binary Model/14.Using the binary classification model to generate predictions.mp45.61MB
  15. 4.2. Binary Model/15.Creating batch predictions in AWS machine learning.mp410.16MB
  16. 4.2. Binary Model/16.Binary classification model environment cleanup.mp42.64MB
  17. 5.3. Multiclass Model/17.Exploring our multiclass model data set.mp48.14MB
  18. 5.3. Multiclass Model/18.Multiclass data preparation.mp411.95MB
  19. 5.3. Multiclass Model/19.AWS multiclass machine learning model.mp46.04MB
  20. 5.3. Multiclass Model/20.Predictions and evaluations of multiclass learning model.mp45.13MB
  21. 5.3. Multiclass Model/21.Generate predictions for AWS multiclass.mp49.34MB
  22. 5.3. Multiclass Model/22.Creating multiclass batch predictions.mp49.85MB
  23. 5.3. Multiclass Model/23.Interpreting batch predictions.mp410.93MB
  24. 5.3. Multiclass Model/24.Clean multiclass model environment.mp42.23MB
  25. 6.4. Regression Model/25.Exploring our regression model data set.mp46.1MB
  26. 6.4. Regression Model/26.Regression data preparation.mp410.32MB
  27. 6.4. Regression Model/27.Creation of an AWS machine learning model.mp43.37MB
  28. 6.4. Regression Model/28.Predictions and evaluations of a machine learning model.mp46.45MB
  29. 6.4. Regression Model/29.Regression batch predictions.mp47.22MB
  30. 6.4. Regression Model/30.Clean regression model environment.mp42.02MB
  31. 7.5. Overview of Other AWS Capabilities/31.SageMaker, Deep Learning AMI, Apache MXNet.mp44.87MB
  32. 8.Conclusion/32.Next steps.mp41.52MB
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