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Udemy - Master Hyperparameter Tuning - Bayesian Optimization and TPE

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Udemy - Master Hyperparameter Tuning - Bayesian Optimization and TPE (Size: 810.4 MB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Bayesian Optimization
  1 - Sequential Search.en_US.srt 7.8 KB
  1 - Sequential Search.ko_KR.srt 6.9 KB
  1 - Sequential Search.mp4 31.9 MB
  1 - Sequential Search.pt_BR.srt 7.5 KB
  1 - Sequential Search.th_TH.srt 16 KB
  1 - Sequential Search.tr_TR.srt 7.4 KB
  1 - Sequential Search.vi_VN.srt 8.9 KB
  10 - Gaussian Process.en_US.srt 17.4 KB
  10 - Gaussian Process.ko_KR.srt 14.2 KB
  10 - Gaussian Process.mp4 58.7 MB
  10 - Gaussian Process.pt_BR.srt 15.5 KB
  10 - Gaussian Process.th_TH.srt 31.7 KB
  10 - Gaussian Process.tr_TR.srt 15.3 KB
  10 - Gaussian Process.vi_VN.srt 19 KB
  11 - Kernels.en_US.srt 8.5 KB
  11 - Kernels.ko_KR.srt 7.2 KB
  11 - Kernels.mp4 19.5 MB
  11 - Kernels.pt_BR.srt 7.6 KB
  11 - Kernels.th_TH.srt 15.8 KB
  11 - Kernels.tr_TR.srt 7.7 KB
  11 - Kernels.vi_VN.srt 9.2 KB
  12 - Acquisition Functions.en_US.srt 17.9 KB
  12 - Acquisition Functions.ko_KR.srt 13.9 KB
  12 - Acquisition Functions.mp4 107.9 MB
  12 - Acquisition Functions.pt_BR.srt 15.6 KB
  12 - Acquisition Functions.th_TH.srt 32 KB
  12 - Acquisition Functions.tr_TR.srt 15.8 KB
  12 - Acquisition Functions.vi_VN.srt 19.3 KB
  13 - Additional Reading Resources.html 6.7 KB
  2 - Course materials.html 5.9 KB
  2 - TPE & SMAC
  14 - Additional SMBO Algorithms.en_US.srt 5.7 KB
  14 - Additional SMBO Algorithms.ko_KR.srt 4.9 KB
  14 - Additional SMBO Algorithms.mp4 12 MB
  14 - Additional SMBO Algorithms.pt_BR.srt 5.1 KB
  14 - Additional SMBO Algorithms.th_TH.srt 10.3 KB
  14 - Additional SMBO Algorithms.tr_TR.srt 5.3 KB
  14 - Additional SMBO Algorithms.vi_VN.srt 6.2 KB
  15 - SMAC.en_US.srt 6.5 KB
  15 - SMAC.mp4 42 MB
  16 - Tree-structured Parzen Estimators - TPE.en_US.srt 4.9 KB
  16 - Tree-structured Parzen Estimators - TPE.ko_KR.srt 4.2 KB
  16 - Tree-structured Parzen Estimators - TPE.mp4 12.6 MB
  16 - Tree-structured Parzen Estimators - TPE.pt_BR.srt 4.2 KB
  16 - Tree-structured Parzen Estimators - TPE.th_TH.srt 8.9 KB
  16 - Tree-structured Parzen Estimators - TPE.tr_TR.srt 4.3 KB
  16 - Tree-structured Parzen Estimators - TPE.vi_VN.srt 5.3 KB
  17 - TPE Procedure.en_US.srt 10.2 KB
  17 - TPE Procedure.ko_KR.srt 8.6 KB
  17 - TPE Procedure.mp4 26.8 MB
  17 - TPE Procedure.pt_BR.srt 9 KB
  17 - TPE Procedure.th_TH.srt 18.9 KB
  17 - TPE Procedure.tr_TR.srt 9.2 KB
  17 - TPE Procedure.vi_VN.srt 11.2 KB
  18 - TPE hyperparameters.en_US.srt 3 KB
  18 - TPE hyperparameters.mp4 20.5 MB
  19 - Bayesian Optimization vs Random Search.en_US.srt 16.8 KB
  19 - Bayesian Optimization vs Random Search.ko_KR.srt 15 KB
  19 - Bayesian Optimization vs Random Search.mp4 58.6 MB
  19 - Bayesian Optimization vs Random Search.pt_BR.srt 15.7 KB
  19 - Bayesian Optimization vs Random Search.th_TH.srt 31.5 KB
  19 - Bayesian Optimization vs Random Search.tr_TR.srt 15.7 KB
  19 - Bayesian Optimization vs Random Search.vi_VN.srt 18.6 KB
  20 - Additional reading resources.html 6.2 KB
  3 - Final bonus section
  21 - Congrats and time to celebrate!.html 6 KB
  22 - Bonus lecture.html 6.1 KB
  3 - Bayesian Optimization.en_US.srt 6.7 KB
  3 - Bayesian Optimization.ko_KR.srt 5.8 KB
  3 - Bayesian Optimization.mp4 35.5 MB
  3 - Bayesian Optimization.pt_BR.srt 6.2 KB
  3 - Bayesian Optimization.th_TH.srt 13 KB
  3 - Bayesian Optimization.tr_TR.srt 6 KB
  3 - Bayesian Optimization.vi_VN.srt 7.1 KB
  4 - Bayesian Inference - Introduction.en_US.srt 10.1 KB
  4 - Bayesian Inference - Introduction.ko_KR.srt 8.3 KB
  4 - Bayesian Inference - Introduction.mp4 44 MB
  4 - Bayesian Inference - Introduction.pt_BR.srt 9.2 KB
  4 - Bayesian Inference - Introduction.th_TH.srt 18.5 KB
  4 - Bayesian Inference - Introduction.tr_TR.srt 8.9 KB
  4 - Bayesian Inference - Introduction.vi_VN.srt 11 KB
  5 - Joint and Conditional Probabilities.en_US.srt 10.3 KB
  5 - Joint and Conditional Probabilities.ko_KR.srt 8.2 KB
  5 - Joint and Conditional Probabilities.mp4 30.5 MB
  5 - Joint and Conditional Probabilities.pt_BR.srt 9.2 KB
  5 - Joint and Conditional Probabilities.th_TH.srt 20.4 KB
  5 - Joint and Conditional Probabilities.tr_TR.srt 9.1 KB
  5 - Joint and Conditional Probabilities.vi_VN.srt 10.8 KB
  6 - Bayes Rule.en_US.srt 15.7 KB
  6 - Bayes Rule.ko_KR.srt 12.6 KB
  6 - Bayes Rule.mp4 57.4 MB
  6 - Bayes Rule.pt_BR.srt 14.3 KB
  6 - Bayes Rule.th_TH.srt 28.9 KB
  6 - Bayes Rule.tr_TR.srt 14.3 KB
  6 - Bayes Rule.vi_VN.srt 16.5 KB
  7 - Sequential Model-Based Optimization.en_US.srt 21.4 KB
  7 - Sequential Model-Based Optimization.ko_KR.srt 18.8 KB
  7 - Sequential Model-Based Optimization.mp4 113.1 MB
  7 - Sequential Model-Based Optimization.pt_BR.srt 19.7 KB
  7 - Sequential Model-Based Optimization.th_TH.srt 39.9 KB
  7 - Sequential Model-Based Optimization.tr_TR.srt 20.1 KB
  7 - Sequential Model-Based Optimization.vi_VN.srt 24.3 KB
  8 - Gaussian Distribution.en_US.srt 9.7 KB
  8 - Gaussian Distribution.ko_KR.srt 7.6 KB
  8 - Gaussian Distribution.mp4 22.5 MB
  8 - Gaussian Distribution.pt_BR.srt 8.6 KB
  8 - Gaussian Distribution.th_TH.srt 16.8 KB
  8 - Gaussian Distribution.tr_TR.srt 8.4 KB
  8 - Gaussian Distribution.vi_VN.srt 10.1 KB
  9 - Multivariate Gaussian Distribution.en_US.srt 21.7 KB
  9 - Multivariate Gaussian Distribution.ko_KR.srt 16.5 KB
  9 - Multivariate Gaussian Distribution.mp4 115.7 MB
  9 - Multivariate Gaussian Distribution.pt_BR.srt 18.7 KB
  9 - Multivariate Gaussian Distribution.th_TH.srt 38.4 KB
  9 - Multivariate Gaussian Distribution.tr_TR.srt 18.6 KB
  9 - Multivariate Gaussian Distribution.vi_VN.srt 22.5 KB

Description


Master Hyperparameter Tuning: Bayesian Optimization & TPE
https://WebToolTip.com
Published 9/2026

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Language: English + subtitle | Duration: 2h 32m | Size: 810.48 MB
Understand how Gaussian processes, acquisition functions and TPE find better model configurations with fewer trials.
What you'll learn

Understand how Bayesian Optimization finds promising hyperparameter configurations

Explain how TPE identifies promising regions of the hyperparameter space

Describe how Gaussian processes model expected performance and uncertainty

Analyze how acquisition functions balance exploration and exploitation

Compare Gaussian process, TPE, and random forest–based optimization
Requirements

Basic understanding of machine learning and common predictive models

Familiarity with hyperparameters and the purpose of model tuning

A general awareness of Grid Search and Random Search is helpful, but not required

Familiarity with machine learning model evaluation metrics

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