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CourseClub NET Coursera Bayesian Methods for Machine Learning

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[CourseClub.NET] Coursera - Bayesian Methods for Machine Learning

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Total Size

2.4 GB

Total Files

133

Hash

D9950C61565FB6179880197913A1B39713C5E252

/001.Introduction to Bayesian methods/

001. Think bayesian & Statistics review.mp4

24.8 MB

001. Think bayesian & Statistics review.srt

10.9 KB

002. Bayesian approach to statistics.mp4

17.9 MB

002. Bayesian approach to statistics.srt

7.1 KB

003. How to define a model.mp4

10.5 MB

003. How to define a model.srt

4.2 KB

004. Example thief & alarm.mp4

62.8 MB

004. Example thief & alarm.srt

12.8 KB

005. Linear regression.mp4

52.5 MB

005. Linear regression.srt

11.5 KB

/002.Conjugate priors/

006. Analytical inference.mp4

14.5 MB

006. Analytical inference.srt

5.0 KB

007. Conjugate distributions.mp4

9.7 MB

007. Conjugate distributions.srt

3.4 KB

008. Example Normal, precision.mp4

17.2 MB

008. Example Normal, precision.srt

6.9 KB

009. Example Bernoulli.mp4

14.7 MB

009. Example Bernoulli.srt

5.6 KB

/003.Latent Variable Models/

010. Latent Variable Models.mp4

38.6 MB

010. Latent Variable Models.srt

15.5 KB

011. Probabilistic clustering.mp4

22.8 MB

011. Probabilistic clustering.srt

8.2 KB

012. Gaussian Mixture Model.mp4

30.6 MB

012. Gaussian Mixture Model.srt

13.2 KB

013. Training GMM.mp4

33.1 MB

013. Training GMM.srt

14.1 KB

014. Example of GMM training.mp4

32.8 MB

014. Example of GMM training.srt

13.5 KB

/004.Expectation Maximization algorithm/

015. Jensen's inequality & Kullback Leibler divergence.mp4

29.7 MB

015. Jensen's inequality & Kullback Leibler divergence.srt

12.2 KB

016. Expectation-Maximization algorithm.mp4

33.5 MB

016. Expectation-Maximization algorithm.srt

13.7 KB

017. E-step details.mp4

69.5 MB

017. E-step details.srt

13.3 KB

018. M-step details.mp4

20.1 MB

018. M-step details.srt

8.2 KB

019. Example EM for discrete mixture, E-step.mp4

59.1 MB

019. Example EM for discrete mixture, E-step.srt

10.4 KB

020. Example EM for discrete mixture, M-step.mp4

68.6 MB

020. Example EM for discrete mixture, M-step.srt

12.7 KB

021. Summary of Expectation Maximization.mp4

21.3 MB

021. Summary of Expectation Maximization.srt

8.3 KB

/005.Applications and examples/

022. General EM for GMM.mp4

65.6 MB

022. General EM for GMM.srt

14.6 KB

023. K-means from probabilistic perspective.mp4

29.8 MB

023. K-means from probabilistic perspective.srt

11.5 KB

024. K-means, M-step.mp4

32.5 MB

024. K-means, M-step.srt

7.4 KB

025. Probabilistic PCA.mp4

40.9 MB

025. Probabilistic PCA.srt

16.4 KB

026. EM for Probabilistic PCA.mp4

22.9 MB

026. EM for Probabilistic PCA.srt

8.9 KB

/006.Variational inference/

027. Why approximate inference.mp4

16.5 MB

027. Why approximate inference.srt

6.4 KB

028. Mean field approximation.mp4

81.1 MB

028. Mean field approximation.srt

11.9 KB

029. Example Ising model.mp4

71.5 MB

029. Example Ising model.srt

17.3 KB

030. Variational EM & Review.mp4

18.2 MB

030. Variational EM & Review.srt

7.8 KB

/007.Latent Dirichlet Allocation/

031. Topic modeling.mp4

17.6 MB

031. Topic modeling.srt

6.7 KB

032. Dirichlet distribution.mp4

21.5 MB

032. Dirichlet distribution.srt

8.4 KB

033. Latent Dirichlet Allocation.mp4

19.1 MB

033. Latent Dirichlet Allocation.srt

6.8 KB

034. LDA E-step, theta.mp4

79.2 MB

034. LDA E-step, theta.srt

9.7 KB

035. LDA E-step, z.mp4

62.1 MB

035. LDA E-step, z.srt

7.7 KB

036. LDA M-step & prediction.mp4

98.0 MB

036. LDA M-step & prediction.srt

11.9 KB

037. Extensions of LDA.mp4

16.6 MB

037. Extensions of LDA.srt

6.3 KB

/008.MCMC/

038. Monte Carlo estimation.mp4

46.7 MB

038. Monte Carlo estimation.srt

17.3 KB

039. Sampling from 1-d distributions.mp4

49.3 MB

039. Sampling from 1-d distributions.srt

16.9 KB

040. Markov Chains.mp4

49.3 MB

040. Markov Chains.srt

16.1 KB

041. Gibbs sampling.mp4

64.4 MB

041. Gibbs sampling.srt

13.2 KB

042. Example of Gibbs sampling.mp4

28.9 MB

042. Example of Gibbs sampling.srt

9.5 KB

043. Metropolis-Hastings.mp4

31.4 MB

043. Metropolis-Hastings.srt

10.0 KB

044. Metropolis-Hastings choosing the critic.mp4

44.0 MB

044. Metropolis-Hastings choosing the critic.srt

9.4 KB

045. Example of Metropolis-Hastings.mp4

38.4 MB

045. Example of Metropolis-Hastings.srt

12.8 KB

046. Markov Chain Monte Carlo summary.mp4

28.1 MB

046. Markov Chain Monte Carlo summary.srt

12.7 KB

047. MCMC for LDA.mp4

49.0 MB

047. MCMC for LDA.srt

21.3 KB

048. Bayesian Neural Networks.mp4

35.7 MB

048. Bayesian Neural Networks.srt

15.2 KB

/009.Variational autoencoders/

049. Scaling Variational Inference & Unbiased estimates.mp4

20.4 MB

049. Scaling Variational Inference & Unbiased estimates.srt

8.4 KB

050. Modeling a distribution of images.mp4

33.8 MB

050. Modeling a distribution of images.srt

14.6 KB

051. Using CNNs with a mixture of Gaussians.mp4

26.1 MB

051. Using CNNs with a mixture of Gaussians.srt

9.9 KB

052. Scaling variational EM.mp4

50.1 MB

052. Scaling variational EM.srt

19.4 KB

053. Gradient of decoder.mp4

20.2 MB

053. Gradient of decoder.srt

7.8 KB

054. Log derivative trick.mp4

21.8 MB

054. Log derivative trick.srt

8.2 KB

055. Reparameterization trick.mp4

26.4 MB

055. Reparameterization trick.srt

9.6 KB

/010.Variational Dropout/

056. Learning with priors.mp4

31.9 MB

056. Learning with priors.srt

8.9 KB

057. Dropout as Bayesian procedure.mp4

36.7 MB

057. Dropout as Bayesian procedure.srt

8.5 KB

058. Sparse variational dropout.mp4

31.1 MB

058. Sparse variational dropout.srt

7.7 KB

/011.Gaussian Processes and Bayesian Optimization/

059. Nonparametric methods.mp4

19.0 MB

059. Nonparametric methods.srt

7.7 KB

060. Gaussian processes.mp4

25.4 MB

060. Gaussian processes.srt

9.9 KB

061. GP for machine learning.mp4

17.1 MB

061. GP for machine learning.srt

6.6 KB

062. Derivation of main formula.mp4

73.3 MB

062. Derivation of main formula.srt

9.7 KB

063. Nuances of GP.mp4

38.6 MB

063. Nuances of GP.srt

14.1 KB

064. Bayesian optimization.mp4

32.7 MB

064. Bayesian optimization.srt

12.8 KB

065. Applications of Bayesian optimization.mp4

17.4 MB

065. Applications of Bayesian optimization.srt

6.2 KB

/

[CourseClub.NET].url

0.1 KB

[FCS Forum].url

0.1 KB

[FreeCourseSite.com].url

0.1 KB

 

Total files 133


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