Create Tool:ruTorrent (PHP Class - Adrien Gibrat)
Create Time:2018-09-09 23:52:30
File Size:2.20 GB
File Count:133
File Hash:f73f5f29c36c9733b8402d09cdaae82fae990737
001.Introduction to Bayesian methods/001. Think bayesian & Statistics review.mp4 | 23.69 MB |
001.Introduction to Bayesian methods/001. Think bayesian & Statistics review.srt | 10.61 KB |
001.Introduction to Bayesian methods/002. Bayesian approach to statistics.mp4 | 17.07 MB |
001.Introduction to Bayesian methods/002. Bayesian approach to statistics.srt | 6.93 KB |
001.Introduction to Bayesian methods/003. How to define a model.mp4 | 10.05 MB |
001.Introduction to Bayesian methods/003. How to define a model.srt | 4.14 KB |
001.Introduction to Bayesian methods/004. Example thief & alarm.mp4 | 59.85 MB |
001.Introduction to Bayesian methods/004. Example thief & alarm.srt | 12.53 KB |
001.Introduction to Bayesian methods/005. Linear regression.mp4 | 50.06 MB |
001.Introduction to Bayesian methods/005. Linear regression.srt | 11.24 KB |
002.Conjugate priors/006. Analytical inference.mp4 | 13.82 MB |
002.Conjugate priors/006. Analytical inference.srt | 4.86 KB |
002.Conjugate priors/007. Conjugate distributions.mp4 | 9.22 MB |
002.Conjugate priors/007. Conjugate distributions.srt | 3.37 KB |
002.Conjugate priors/008. Example Normal, precision.mp4 | 16.41 MB |
002.Conjugate priors/008. Example Normal, precision.srt | 6.72 KB |
002.Conjugate priors/009. Example Bernoulli.mp4 | 14.02 MB |
002.Conjugate priors/009. Example Bernoulli.srt | 5.44 KB |
003.Latent Variable Models/010. Latent Variable Models.mp4 | 36.78 MB |
003.Latent Variable Models/010. Latent Variable Models.srt | 15.14 KB |
003.Latent Variable Models/011. Probabilistic clustering.mp4 | 21.70 MB |
003.Latent Variable Models/011. Probabilistic clustering.srt | 8.04 KB |
003.Latent Variable Models/012. Gaussian Mixture Model.mp4 | 29.16 MB |
003.Latent Variable Models/012. Gaussian Mixture Model.srt | 12.90 KB |
003.Latent Variable Models/013. Training GMM.mp4 | 31.61 MB |
003.Latent Variable Models/013. Training GMM.srt | 13.74 KB |
003.Latent Variable Models/014. Example of GMM training.mp4 | 31.27 MB |
003.Latent Variable Models/014. Example of GMM training.srt | 13.15 KB |
004.Expectation Maximization algorithm/015. Jensen's inequality & Kullback Leibler divergence.mp4 | 28.36 MB |
004.Expectation Maximization algorithm/015. Jensen's inequality & Kullback Leibler divergence.srt | 11.87 KB |
004.Expectation Maximization algorithm/016. Expectation-Maximization algorithm.mp4 | 31.97 MB |
004.Expectation Maximization algorithm/016. Expectation-Maximization algorithm.srt | 13.37 KB |
004.Expectation Maximization algorithm/017. E-step details.mp4 | 66.24 MB |
004.Expectation Maximization algorithm/017. E-step details.srt | 12.96 KB |
004.Expectation Maximization algorithm/018. M-step details.mp4 | 19.21 MB |
004.Expectation Maximization algorithm/018. M-step details.srt | 8.00 KB |
004.Expectation Maximization algorithm/019. Example EM for discrete mixture, E-step.mp4 | 56.37 MB |
004.Expectation Maximization algorithm/019. Example EM for discrete mixture, E-step.srt | 10.13 KB |
004.Expectation Maximization algorithm/020. Example EM for discrete mixture, M-step.mp4 | 65.47 MB |
004.Expectation Maximization algorithm/020. Example EM for discrete mixture, M-step.srt | 12.37 KB |
004.Expectation Maximization algorithm/021. Summary of Expectation Maximization.mp4 | 20.29 MB |
004.Expectation Maximization algorithm/021. Summary of Expectation Maximization.srt | 8.07 KB |
005.Applications and examples/022. General EM for GMM.mp4 | 62.53 MB |
005.Applications and examples/022. General EM for GMM.srt | 14.24 KB |
005.Applications and examples/023. K-means from probabilistic perspective.mp4 | 28.46 MB |
005.Applications and examples/023. K-means from probabilistic perspective.srt | 11.20 KB |
005.Applications and examples/024. K-means, M-step.mp4 | 30.95 MB |
005.Applications and examples/024. K-means, M-step.srt | 7.18 KB |
005.Applications and examples/025. Probabilistic PCA.mp4 | 38.98 MB |
005.Applications and examples/025. Probabilistic PCA.srt | 16.02 KB |
005.Applications and examples/026. EM for Probabilistic PCA.mp4 | 21.80 MB |
005.Applications and examples/026. EM for Probabilistic PCA.srt | 8.67 KB |
006.Variational inference/027. Why approximate inference.mp4 | 15.74 MB |
006.Variational inference/027. Why approximate inference.srt | 6.28 KB |
006.Variational inference/028. Mean field approximation.mp4 | 77.30 MB |
006.Variational inference/028. Mean field approximation.srt | 11.66 KB |
006.Variational inference/029. Example Ising model.mp4 | 68.23 MB |
006.Variational inference/029. Example Ising model.srt | 16.86 KB |
006.Variational inference/030. Variational EM & Review.mp4 | 17.38 MB |
006.Variational inference/030. Variational EM & Review.srt | 7.58 KB |
007.Latent Dirichlet Allocation/031. Topic modeling.mp4 | 16.76 MB |
007.Latent Dirichlet Allocation/031. Topic modeling.srt | 6.59 KB |
007.Latent Dirichlet Allocation/032. Dirichlet distribution.mp4 | 20.49 MB |
007.Latent Dirichlet Allocation/032. Dirichlet distribution.srt | 8.17 KB |
007.Latent Dirichlet Allocation/033. Latent Dirichlet Allocation.mp4 | 18.22 MB |
007.Latent Dirichlet Allocation/033. Latent Dirichlet Allocation.srt | 6.65 KB |
007.Latent Dirichlet Allocation/034. LDA E-step, theta.mp4 | 75.56 MB |
007.Latent Dirichlet Allocation/034. LDA E-step, theta.srt | 9.42 KB |
007.Latent Dirichlet Allocation/035. LDA E-step, z.mp4 | 59.22 MB |
007.Latent Dirichlet Allocation/035. LDA E-step, z.srt | 7.48 KB |
007.Latent Dirichlet Allocation/036. LDA M-step & prediction.mp4 | 93.47 MB |
007.Latent Dirichlet Allocation/036. LDA M-step & prediction.srt | 11.63 KB |
007.Latent Dirichlet Allocation/037. Extensions of LDA.mp4 | 15.83 MB |
007.Latent Dirichlet Allocation/037. Extensions of LDA.srt | 6.17 KB |
008.MCMC/038. Monte Carlo estimation.mp4 | 44.51 MB |
008.MCMC/038. Monte Carlo estimation.srt | 16.89 KB |
008.MCMC/039. Sampling from 1-d distributions.mp4 | 47.05 MB |
008.MCMC/039. Sampling from 1-d distributions.srt | 16.47 KB |
008.MCMC/040. Markov Chains.mp4 | 47.06 MB |
008.MCMC/040. Markov Chains.srt | 15.71 KB |
008.MCMC/041. Gibbs sampling.mp4 | 61.41 MB |
008.MCMC/041. Gibbs sampling.srt | 12.88 KB |
008.MCMC/042. Example of Gibbs sampling.mp4 | 27.59 MB |
008.MCMC/042. Example of Gibbs sampling.srt | 9.29 KB |
008.MCMC/043. Metropolis-Hastings.mp4 | 29.90 MB |
008.MCMC/043. Metropolis-Hastings.srt | 9.74 KB |
008.MCMC/044. Metropolis-Hastings choosing the critic.mp4 | 42.01 MB |
008.MCMC/044. Metropolis-Hastings choosing the critic.srt | 9.19 KB |
008.MCMC/045. Example of Metropolis-Hastings.mp4 | 36.61 MB |
008.MCMC/045. Example of Metropolis-Hastings.srt | 12.47 KB |
008.MCMC/046. Markov Chain Monte Carlo summary.mp4 | 26.83 MB |
008.MCMC/046. Markov Chain Monte Carlo summary.srt | 12.37 KB |
008.MCMC/047. MCMC for LDA.mp4 | 46.68 MB |
008.MCMC/047. MCMC for LDA.srt | 20.83 KB |
008.MCMC/048. Bayesian Neural Networks.mp4 | 34.03 MB |
008.MCMC/048. Bayesian Neural Networks.srt | 14.81 KB |
009.Variational autoencoders/049. Scaling Variational Inference & Unbiased estimates.mp4 | 19.50 MB |
009.Variational autoencoders/049. Scaling Variational Inference & Unbiased estimates.srt | 8.25 KB |
009.Variational autoencoders/050. Modeling a distribution of images.mp4 | 32.24 MB |
009.Variational autoencoders/050. Modeling a distribution of images.srt | 14.23 KB |
009.Variational autoencoders/051. Using CNNs with a mixture of Gaussians.mp4 | 24.85 MB |
009.Variational autoencoders/051. Using CNNs with a mixture of Gaussians.srt | 9.70 KB |
009.Variational autoencoders/052. Scaling variational EM.mp4 | 47.78 MB |
009.Variational autoencoders/052. Scaling variational EM.srt | 18.92 KB |
009.Variational autoencoders/053. Gradient of decoder.mp4 | 19.31 MB |
009.Variational autoencoders/053. Gradient of decoder.srt | 7.63 KB |
009.Variational autoencoders/054. Log derivative trick.mp4 | 20.79 MB |
009.Variational autoencoders/054. Log derivative trick.srt | 7.98 KB |
009.Variational autoencoders/055. Reparameterization trick.mp4 | 25.18 MB |
009.Variational autoencoders/055. Reparameterization trick.srt | 9.37 KB |
010.Variational Dropout/056. Learning with priors.mp4 | 30.39 MB |
010.Variational Dropout/056. Learning with priors.srt | 8.72 KB |
010.Variational Dropout/057. Dropout as Bayesian procedure.mp4 | 35.03 MB |
010.Variational Dropout/057. Dropout as Bayesian procedure.srt | 8.34 KB |
010.Variational Dropout/058. Sparse variational dropout.mp4 | 29.61 MB |
010.Variational Dropout/058. Sparse variational dropout.srt | 7.50 KB |
011.Gaussian Processes and Bayesian Optimization/059. Nonparametric methods.mp4 | 18.16 MB |
011.Gaussian Processes and Bayesian Optimization/059. Nonparametric methods.srt | 7.49 KB |
011.Gaussian Processes and Bayesian Optimization/060. Gaussian processes.mp4 | 24.18 MB |
011.Gaussian Processes and Bayesian Optimization/060. Gaussian processes.srt | 9.63 KB |
011.Gaussian Processes and Bayesian Optimization/061. GP for machine learning.mp4 | 16.36 MB |
011.Gaussian Processes and Bayesian Optimization/061. GP for machine learning.srt | 6.41 KB |
011.Gaussian Processes and Bayesian Optimization/062. Derivation of main formula.mp4 | 69.86 MB |
011.Gaussian Processes and Bayesian Optimization/062. Derivation of main formula.srt | 9.46 KB |
011.Gaussian Processes and Bayesian Optimization/063. Nuances of GP.mp4 | 36.81 MB |
011.Gaussian Processes and Bayesian Optimization/063. Nuances of GP.srt | 13.79 KB |
011.Gaussian Processes and Bayesian Optimization/064. Bayesian optimization.mp4 | 31.23 MB |
011.Gaussian Processes and Bayesian Optimization/064. Bayesian optimization.srt | 12.53 KB |
011.Gaussian Processes and Bayesian Optimization/065. Applications of Bayesian optimization.mp4 | 16.61 MB |
011.Gaussian Processes and Bayesian Optimization/065. Applications of Bayesian optimization.srt | 6.06 KB |
[FreeCoursesOnline.Me].url | 133 B |
[FreeTutorials.Us].url | 119 B |
[FTU Forum].url | 252 B |
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