[ WebToolTip.com ] Coursera - Applied Bayesian Data Analysis Specialization
[ WebToolTip.com ] Coursera - Applied Bayesian Data Analysis Specialization metadata, size 1333.51 MB, 307 files, category video, indexed at 2026-06-14.
资源标识
Infohash0aa60fb135a7f3a5474b04d44bdb822fdc75f519
总大小1.3 GB
格式mp4
分类视频
文件数307
发掘时间（北京时间）2026-06-14 09:14:28
最后活跃（北京时间）2026-06-14 09:15:14
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完整磁力链接
magnet:?xt=urn:btih:0aa60fb135a7f3a5474b04d44bdb822fdc75f519&dn=%5B%20WebToolTip.com%20%5D%20Coursera%20-%20Applied%20Bayesian%20Data%20Analysis%20Specialization
迅雷地址
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjBhYTYwZmIxMzVhN2YzYTU0NzRiMDRkNDRiZGI4MjJmZGM3NWY1MTkmZG49JTVCJTIwV2ViVG9vbFRpcC5jb20lMjAlNUQlMjBDb3Vyc2VyYSUyMC0lMjBBcHBsaWVkJTIwQmF5ZXNpYW4lMjBEYXRhJTIwQW5hbHlzaXMlMjBTcGVjaWFsaXphdGlvblpa
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Tag
文件列表
| 文件名 | 格式 | 大小 |
|---|---|---|
| Get Bonus Downloads Here.url | url | 180 B |
| Bonus Resources.txt | txt | 70 B |
| 01_course-overview_instructions.html | html | 13.7 KB |
| 02_technical-and-accessibility-support_instructions.html | html | 2.3 KB |
| 03_advanced-bayesian-inference-and-decision-making.en.srt | srt | 4.3 KB |
| 03_advanced-bayesian-inference-and-decision-making.en.txt | txt | 2.8 KB |
| 03_advanced-bayesian-inference-and-decision-making.mp4 | mp4 | 60.1 MB |
| 04_why-do-we-need-variational-inference.en.srt | srt | 4.4 KB |
| 04_why-do-we-need-variational-inference.en.txt | txt | 2.8 KB |
| 04_why-do-we-need-variational-inference.mp4 | mp4 | 11.6 MB |
| 04_why-do-we-need-variational-inference_ABAM9V2_Why_VI.pptx | pptx | 144.1 KB |
| 05_core-of-variational-inference.en.srt | srt | 7.8 KB |
| 05_core-of-variational-inference.en.txt | txt | 5.1 KB |
| 05_core-of-variational-inference.mp4 | mp4 | 23.3 MB |
| 05_core-of-variational-inference_ABAM9V3_VI_core.pptx | pptx | 2.4 MB |
| 06_kullback-leibler-divergence_instructions.html | html | 253.3 KB |
| 01_mean-field-approximation.en.srt | srt | 4.8 KB |
| 01_mean-field-approximation.en.txt | txt | 3.1 KB |
| 01_mean-field-approximation.mp4 | mp4 | 13.5 MB |
| 01_mean-field-approximation_ABAM9V4_Mean_field_approximation.pptx | pptx | 4.4 MB |
| 02_multimodal-learning_instructions.html | html | 2.2 KB |
| 03_vi-vs-mcmc.en.srt | srt | 4.8 KB |
| 03_vi-vs-mcmc.en.txt | txt | 3.5 KB |
| 03_vi-vs-mcmc.mp4 | mp4 | 17.5 MB |
| 03_vi-vs-mcmc_ABAM9V5_VI_vs_MCMC.pptx | pptx | 1.9 MB |
| 01_module-wrap-up_instructions.html | html | 1.5 KB |
| 02_recommended-learning-resources_instructions.html | html | 2.0 KB |
| 01_bayesian-decision-theory.en.srt | srt | 5.0 KB |
| 01_bayesian-decision-theory.en.txt | txt | 3.2 KB |
| 01_bayesian-decision-theory.mp4 | mp4 | 14.3 MB |
| 01_bayesian-decision-theory_ABAM10V1_Basics_Bayesian_decision_theory.pptx | pptx | 163.8 KB |
| 02_the-role-of-loss-function.en.srt | srt | 7.7 KB |
| 02_the-role-of-loss-function.en.txt | txt | 4.9 KB |
| 02_the-role-of-loss-function.mp4 | mp4 | 23.7 MB |
| 02_the-role-of-loss-function_ABAM10V2_loss_function.pptx | pptx | 200.8 KB |
| 03_realistic-loss-functions_instructions.html | html | 4.9 KB |
| 01_multi-objective-loss-functions.en.srt | srt | 6.4 KB |
| 01_multi-objective-loss-functions.en.txt | txt | 4.2 KB |
| 01_multi-objective-loss-functions.mp4 | mp4 | 21.2 MB |
| 01_multi-objective-loss-functions_ABAM10V3_Multi_objective_loss_function.pptx | pptx | 289.9 KB |
| 02_prediction-as-a-decision-problem_instructions.html | html | 280.5 KB |
| 03_connection-with-machine-learning.en.srt | srt | 5.9 KB |
| 03_connection-with-machine-learning.en.txt | txt | 4.3 KB |
| 03_connection-with-machine-learning.mp4 | mp4 | 22.5 MB |
| 03_connection-with-machine-learning_ABAM10V4_connection_with_ML.pptx | pptx | 158.8 KB |
| 01_module-wrap-up_instructions.html | html | 1.8 KB |
| 01_module-wrap-up_losses-and-decision-making.html | html | 73.0 KB |
| 01_non-parametric-models-flexibility.en.srt | srt | 6.1 KB |
| 01_non-parametric-models-flexibility.en.txt | txt | 4.0 KB |
| 01_non-parametric-models-flexibility.mp4 | mp4 | 17.8 MB |
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