zhongziso
搜索
zhongziso
首页
首页
功能
磁力转BT
BT转磁力
关于
使用教程
免责声明
磁力助手
Advanced Machine Learning Specialization
magnet:?xt=urn:btih:9a31f0c4690810429c38e93ef0b80ae51a3b6840&dn=Advanced Machine Learning Specialization
磁力链接详情
文件列表详情
9a31f0c4690810429c38e93ef0b80ae51a3b6840
infohash:
159
文件数量
2.85 GB
文件大小
2019-3-31 10:39
创建日期
2024-6-28 09:44
最后访问
相关分词
Advanced
Machine
Learning
Specialization
3. bayesian-methods-in-machine-learning/01_introduction-to-bayesian-methods-conjugate-priors/02_conjugate-priors/02_conjugate-distributions.mp4 5.33 MB
3. bayesian-methods-in-machine-learning/01_introduction-to-bayesian-methods-conjugate-priors/01_introduction-to-bayesian-methods/03_how-to-define-a-model.mp4 5.85 MB
3. bayesian-methods-in-machine-learning/01_introduction-to-bayesian-methods-conjugate-priors/02_conjugate-priors/01_analytical-inference.mp4 7.62 MB
2. competitive-data-science/11_ensembling/01_ensembling/01_introduction-into-ensemble-methods.mp4 8 MB
3. bayesian-methods-in-machine-learning/01_introduction-to-bayesian-methods-conjugate-priors/02_conjugate-priors/04_example-bernoulli.mp4 8.03 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/02_latent-dirichlet-allocation/07_extensions-of-lda.mp4 9.17 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/01_variational-inference/01_why-approximate-inference.mp4 9.2 MB
2. competitive-data-science/03_final-project-description/01_final-project/02_final-project-overview.mp4 9.31 MB
3. bayesian-methods-in-machine-learning/06_gaussian-processes-bayesian-optimization/01_gaussian-processes-and-bayesian-optimization/07_application-of-bayesian-optimization.mp4 9.55 MB
3. bayesian-methods-in-machine-learning/01_introduction-to-bayesian-methods-conjugate-priors/02_conjugate-priors/03_example-normal-precision.mp4 9.57 MB
3. bayesian-methods-in-machine-learning/06_gaussian-processes-bayesian-optimization/01_gaussian-processes-and-bayesian-optimization/03_gp-for-machine-learning.mp4 9.63 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/02_latent-dirichlet-allocation/01_topic-modeling.mp4 9.7 MB
3. bayesian-methods-in-machine-learning/01_introduction-to-bayesian-methods-conjugate-priors/01_introduction-to-bayesian-methods/02_bayesian-approach-to-statistics.mp4 9.77 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/01_variational-inference/04_variational-em-review.mp4 10.14 MB
1. intro-to-deep-learning/01_introduction-to-optimization/02_linear-model-as-the-simplest-neural-network/03_gradient-descent.mp4 10.25 MB
3. bayesian-methods-in-machine-learning/06_gaussian-processes-bayesian-optimization/01_gaussian-processes-and-bayesian-optimization/01_nonparametric-methods.mp4 10.54 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/02_latent-dirichlet-allocation/03_latent-dirichlet-allocation.mp4 10.56 MB
1. intro-to-deep-learning/03_deep-learning-for-images/03_applications-of-cnns/01_learning-new-tasks-with-pre-trained-cnns.mp4 10.67 MB
1. intro-to-deep-learning/01_introduction-to-optimization/03_regularization-in-machine-learning/02_model-regularization.mp4 10.75 MB
2. competitive-data-science/01_introduction-recap/02_competition-mechanics/03_real-world-application-vs-competitions.mp4 11.02 MB
2. competitive-data-science/10_advanced-feature-engineering-ii/01_advanced-features-ii/03_feature-interactions.mp4 11.11 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/01_variational-autoencoders/05_gradient-of-decoder.mp4 11.34 MB
1. intro-to-deep-learning/01_introduction-to-optimization/04_stochastic-methods-for-optimization/01_stochastic-gradient-descent.mp4 11.4 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/02_expectation-maximization-algorithm/04_m-step-details.mp4 11.43 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/01_variational-autoencoders/01_scaling-variational-inference-unbiased-estimates.mp4 11.49 MB
2. competitive-data-science/10_advanced-feature-engineering-ii/01_advanced-features-ii/01_statistics-and-distance-based-features.mp4 11.6 MB
2. competitive-data-science/10_advanced-feature-engineering-ii/01_advanced-features-ii/04_t-sne.mp4 11.62 MB
2. competitive-data-science/01_introduction-recap/04_software-hardware-requirements/01_software-hardware-requirements.mp4 11.75 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/02_latent-dirichlet-allocation/02_dirichlet-distribution.mp4 11.88 MB
1. intro-to-deep-learning/04_unsupervised-representation-learning/01_intro-to-unsupervised-learning/02_autoencoders-101.mp4 11.9 MB
2. competitive-data-science/11_ensembling/01_ensembling/02_bagging.mp4 11.94 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/02_expectation-maximization-algorithm/07_summary-of-expectation-maximization.mp4 12.1 MB
2. competitive-data-science/04_exploratory-data-analysis/02_eda-examples/03_numerai-competition-eda.mp4 12.21 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/01_variational-autoencoders/06_log-derivative-trick.mp4 12.24 MB
2. competitive-data-science/06_data-leakages/01_data-leakages/01_basic-data-leaks.mp4 12.28 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/01_latent-variable-models/02_probabilistic-clustering.mp4 12.4 MB
2. competitive-data-science/04_exploratory-data-analysis/01_exploratory-data-analysis/03_building-intuition-about-the-data.mp4 12.7 MB
1. intro-to-deep-learning/04_unsupervised-representation-learning/01_intro-to-unsupervised-learning/01_unsupervised-learning-what-it-is-and-why-bother.mp4 12.74 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/03_applications-and-examples/05_em-for-probabilistic-pca.mp4 12.98 MB
2. competitive-data-science/07_metrics-optimization/01_metrics-optimization/06_general-approaches-for-metrics-optimization.mp4 13.12 MB
2. competitive-data-science/10_advanced-feature-engineering-ii/01_advanced-features-ii/02_matrix-factorizations.mp4 13.16 MB
2. competitive-data-science/04_exploratory-data-analysis/02_eda-examples/01_springleaf-competition-eda-i.mp4 13.18 MB
2. competitive-data-science/12_competitions-go-through/01_competitions-go-through/03_springleaf-marketing-response.mp4 13.29 MB
1. intro-to-deep-learning/02_introduction-to-neural-networks/01_multilayer-perceptron-or-the-basic-principles-of-deep-learning/01_multilayer-perceptron.mp4 13.4 MB
2. competitive-data-science/04_exploratory-data-analysis/01_exploratory-data-analysis/02_exploratory-data-analysis.mp4 13.51 MB
3. bayesian-methods-in-machine-learning/01_introduction-to-bayesian-methods-conjugate-priors/01_introduction-to-bayesian-methods/01_think-bayesian-statistics-review.mp4 13.55 MB
1. intro-to-deep-learning/01_introduction-to-optimization/04_stochastic-methods-for-optimization/02_gradient-descent-extensions.mp4 13.63 MB
1. intro-to-deep-learning/02_introduction-to-neural-networks/04_philosophy-of-deep-learning/02_deep-learning-as-a-language.mp4 13.66 MB
2. competitive-data-science/01_introduction-recap/02_competition-mechanics/01_competition-mechanics.mp4 13.69 MB
2. competitive-data-science/09_hyperparameter-optimization/01_hyperparameter-tuning/02_hyperparameter-tuning-i.mp4 13.73 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/02_variational-dropout/03_sparse-variational-dropout.mp4 13.76 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/02_variational-dropout/01_learning-with-priors.mp4 13.81 MB
1. intro-to-deep-learning/02_introduction-to-neural-networks/01_multilayer-perceptron-or-the-basic-principles-of-deep-learning/02_training-a-neural-network.mp4 13.95 MB
2. competitive-data-science/07_metrics-optimization/01_metrics-optimization/09_classification-metrics-optimization-ii.mp4 13.96 MB
2. competitive-data-science/02_feature-preprocessing-and-generation-with-respect-to-models/01_feature-preprocessing-and-generation-with-respect-to-models/01_overview.mp4 14.08 MB
3. bayesian-methods-in-machine-learning/06_gaussian-processes-bayesian-optimization/01_gaussian-processes-and-bayesian-optimization/02_gaussian-processes.mp4 14.14 MB
2. competitive-data-science/05_validation/01_validation/02_validation-strategies.mp4 14.19 MB
1. intro-to-deep-learning/01_introduction-to-optimization/03_regularization-in-machine-learning/01_overfitting-problem-and-model-validation.mp4 14.22 MB
1. intro-to-deep-learning/05_deep-learning-for-sequences/02_modern-rnns/01_the-training-of-rnns-is-not-that-easy.mp4 14.51 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/01_variational-autoencoders/03_using-cnns-with-a-mixture-of-gaussians.mp4 14.61 MB
1. intro-to-deep-learning/04_unsupervised-representation-learning/04_generative-adversarial-networks/01_generative-models-101.mp4 14.62 MB
2. competitive-data-science/04_exploratory-data-analysis/01_exploratory-data-analysis/06_dataset-cleaning-and-other-things-to-check.mp4 14.7 MB
2. competitive-data-science/07_metrics-optimization/01_metrics-optimization/08_classification-metrics-optimization-i.mp4 14.71 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/01_variational-autoencoders/07_reparameterization-trick.mp4 14.74 MB
1. intro-to-deep-learning/02_introduction-to-neural-networks/01_multilayer-perceptron-or-the-basic-principles-of-deep-learning/03_backpropagation-primer.mp4 14.96 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/03_applications-and-examples/03_k-means-m-step.mp4 15.26 MB
1. intro-to-deep-learning/04_unsupervised-representation-learning/02_more-autoencoders/02_autoencoder-applications-image-generation-data-visualization-more.mp4 15.33 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/02_variational-dropout/02_dropout-as-bayesian-procedure.mp4 15.47 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/05_example-of-gibbs-sampling.mp4 15.54 MB
2. competitive-data-science/08_advanced-feature-engineering-i/01_mean-encodings/02_regularization.mp4 15.63 MB
1. intro-to-deep-learning/02_introduction-to-neural-networks/02_tensorflow/03_gradients-optimization-in-tensorflow.mp4 15.65 MB
2. competitive-data-science/07_metrics-optimization/01_metrics-optimization/02_motivation.mp4 15.76 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/09_markov-chain-monte-carlo-summary.mp4 15.83 MB
1. intro-to-deep-learning/05_deep-learning-for-sequences/01_introduction-to-rnn/01_motivation-for-recurrent-layers.mp4 15.99 MB
2. competitive-data-science/12_competitions-go-through/01_competitions-go-through/05_walmart-trip-type-classification.mp4 16.29 MB
1. intro-to-deep-learning/02_introduction-to-neural-networks/04_philosophy-of-deep-learning/01_what-deep-learning-is-and-is-not.mp4 16.32 MB
2. competitive-data-science/07_metrics-optimization/01_metrics-optimization/04_regression-metrics-review-ii.mp4 16.61 MB
1. intro-to-deep-learning/03_deep-learning-for-images/03_applications-of-cnns/02_a-glimpse-of-other-computer-vision-tasks.mp4 16.86 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/06_metropolis-hastings.mp4 16.86 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/02_expectation-maximization-algorithm/01_jensens-inequality-kullback-leibler-divergence.mp4 16.87 MB
2. competitive-data-science/08_advanced-feature-engineering-i/01_mean-encodings/01_concept-of-mean-encoding.mp4 16.92 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/03_applications-and-examples/02_k-means-from-probabilistic-perspective.mp4 16.93 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/01_latent-variable-models/03_gaussian-mixture-model.mp4 17.5 MB
2. competitive-data-science/01_introduction-recap/01_welcome-to-how-to-win-a-data-science-competition/02_course-overview.mp4 17.6 MB
1. intro-to-deep-learning/03_deep-learning-for-images/02_modern-cnns/02_overview-of-modern-cnn-architectures.mp4 17.7 MB
2. competitive-data-science/02_feature-preprocessing-and-generation-with-respect-to-models/01_feature-preprocessing-and-generation-with-respect-to-models/04_datetime-and-coordinates.mp4 17.73 MB
3. bayesian-methods-in-machine-learning/06_gaussian-processes-bayesian-optimization/01_gaussian-processes-and-bayesian-optimization/06_bayesian-optimization.mp4 18.17 MB
2. competitive-data-science/01_introduction-recap/02_competition-mechanics/02_kaggle-overview-screencast.mp4 18.32 MB
2. competitive-data-science/01_introduction-recap/03_recap-of-main-ml-algorithms/01_recap-of-main-ml-algorithms.mp4 18.32 MB
1. intro-to-deep-learning/05_deep-learning-for-sequences/01_introduction-to-rnn/02_simple-rnn-and-backpropagation.mp4 18.36 MB
1. intro-to-deep-learning/02_introduction-to-neural-networks/03_keras/01_keras-introduction.mp4 18.51 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/01_latent-variable-models/05_example-of-gmm-training.mp4 18.53 MB
1. intro-to-deep-learning/05_deep-learning-for-sequences/02_modern-rnns/02_dealing-with-vanishing-and-exploding-gradients.mp4 18.65 MB
2. competitive-data-science/05_validation/01_validation/01_validation-and-overfitting.mp4 18.82 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/01_latent-variable-models/04_training-gmm.mp4 18.87 MB
2. competitive-data-science/06_data-leakages/01_data-leakages/02_leaderboard-probing-and-examples-of-rare-data-leaks.mp4 18.92 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/01_variational-autoencoders/02_modeling-a-distribution-of-images.mp4 18.98 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/02_expectation-maximization-algorithm/02_expectation-maximization-algorithm.mp4 19.01 MB
1. intro-to-deep-learning/02_introduction-to-neural-networks/02_tensorflow/01_going-deeper-with-tensorflow.mp4 19.14 MB
1. intro-to-deep-learning/01_introduction-to-optimization/02_linear-model-as-the-simplest-neural-network/01_linear-regression.mp4 19.18 MB
2. competitive-data-science/06_data-leakages/01_data-leakages/03_expedia-challenge.mp4 19.49 MB
2. competitive-data-science/11_ensembling/01_ensembling/06_ensembling-tips-and-tricks.mp4 19.55 MB
1. intro-to-deep-learning/04_unsupervised-representation-learning/04_generative-adversarial-networks/02_generative-adversarial-networks.mp4 19.79 MB
2. competitive-data-science/07_metrics-optimization/01_metrics-optimization/07_regression-metrics-optimization.mp4 19.95 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/11_bayesian-neural-networks.mp4 20.02 MB
2. competitive-data-science/12_competitions-go-through/01_competitions-go-through/02_crowdflower-competition.mp4 20.14 MB
1. intro-to-deep-learning/04_unsupervised-representation-learning/03_word-embeddings/01_natural-language-processing-primer.mp4 20.21 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/07_metropolis-hastings-choosing-the-critic.mp4 20.27 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/08_example-of-metropolis-hastings.mp4 20.49 MB
1. intro-to-deep-learning/04_unsupervised-representation-learning/02_more-autoencoders/01_autoencoder-applications.mp4 20.53 MB
2. competitive-data-science/02_feature-preprocessing-and-generation-with-respect-to-models/01_feature-preprocessing-and-generation-with-respect-to-models/05_handling-missing-values.mp4 20.93 MB
3. bayesian-methods-in-machine-learning/06_gaussian-processes-bayesian-optimization/01_gaussian-processes-and-bayesian-optimization/05_nuances-of-gp.mp4 21.26 MB
2. competitive-data-science/02_feature-preprocessing-and-generation-with-respect-to-models/02_feature-extraction-from-text-and-images/01_bag-of-words.mp4 21.3 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/01_latent-variable-models/01_latent-variable-models.mp4 21.31 MB
2. competitive-data-science/11_ensembling/01_ensembling/05_stacknet.mp4 21.4 MB
2. competitive-data-science/11_ensembling/01_ensembling/03_boosting.mp4 21.56 MB
2. competitive-data-science/08_advanced-feature-engineering-i/01_mean-encodings/03_extensions-and-generalizations.mp4 21.68 MB
2. competitive-data-science/02_feature-preprocessing-and-generation-with-respect-to-models/01_feature-preprocessing-and-generation-with-respect-to-models/03_categorical-and-ordinal-features.mp4 22.28 MB
1. intro-to-deep-learning/04_unsupervised-representation-learning/04_generative-adversarial-networks/03_applications-of-adversarial-approach.mp4 22.79 MB
1. intro-to-deep-learning/03_deep-learning-for-images/01_introduction-to-cnn/01_motivation-for-convolutional-layers.mp4 22.79 MB
1. intro-to-deep-learning/01_introduction-to-optimization/02_linear-model-as-the-simplest-neural-network/02_linear-classification.mp4 22.82 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/03_applications-and-examples/04_probabilistic-pca.mp4 23.12 MB
1. intro-to-deep-learning/03_deep-learning-for-images/01_introduction-to-cnn/02_our-first-cnn-architecture.mp4 23.28 MB
2. competitive-data-science/11_ensembling/01_ensembling/04_stacking.mp4 23.3 MB
2. competitive-data-science/09_hyperparameter-optimization/01_hyperparameter-tuning/03_hyperparameter-tuning-ii.mp4 23.79 MB
2. competitive-data-science/04_exploratory-data-analysis/01_exploratory-data-analysis/05_visualizations.mp4 23.89 MB
3. bayesian-methods-in-machine-learning/01_introduction-to-bayesian-methods-conjugate-priors/01_introduction-to-bayesian-methods/05_linear-regression.mp4 24.35 MB
1. intro-to-deep-learning/05_deep-learning-for-sequences/02_modern-rnns/03_modern-rnns-lstm-and-gru.mp4 24.55 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/01_monte-carlo-estimation.mp4 25.13 MB
2. competitive-data-science/09_hyperparameter-optimization/01_hyperparameter-tuning/04_hyperparameter-tuning-iii.mp4 25.68 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/02_expectation-maximization-algorithm/05_example-em-for-discrete-mixture-e-step.mp4 25.69 MB
2. competitive-data-science/02_feature-preprocessing-and-generation-with-respect-to-models/02_feature-extraction-from-text-and-images/02_word2vec-cnn.mp4 25.84 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/02_latent-dirichlet-allocation/05_lda-e-step-z.mp4 26.09 MB
2. competitive-data-science/04_exploratory-data-analysis/01_exploratory-data-analysis/04_exploring-anonymized-data.mp4 26.31 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/03_markov-chains.mp4 26.45 MB
1. intro-to-deep-learning/04_unsupervised-representation-learning/03_word-embeddings/02_word-embeddings.mp4 26.45 MB
2. competitive-data-science/07_metrics-optimization/01_metrics-optimization/03_regression-metrics-review-i.mp4 26.45 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/02_sampling-from-1-d-distributions.mp4 26.59 MB
2. competitive-data-science/02_feature-preprocessing-and-generation-with-respect-to-models/01_feature-preprocessing-and-generation-with-respect-to-models/02_numeric-features.mp4 26.85 MB
2. competitive-data-science/04_exploratory-data-analysis/02_eda-examples/02_springleaf-competition-eda-ii.mp4 27.56 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/10_mcmc-for-lda.mp4 27.63 MB
3. bayesian-methods-in-machine-learning/01_introduction-to-bayesian-methods-conjugate-priors/01_introduction-to-bayesian-methods/04_example-thief-alarm.mp4 27.67 MB
3. bayesian-methods-in-machine-learning/05_variational-autoencoder/01_variational-autoencoders/04_scaling-variational-em.mp4 27.69 MB
1. intro-to-deep-learning/05_deep-learning-for-sequences/03_applications-of-rnns/01_practical-use-cases-for-rnns.mp4 29.11 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/02_expectation-maximization-algorithm/06_example-em-for-discrete-mixture-m-step.mp4 29.3 MB
3. bayesian-methods-in-machine-learning/04_markov-chain-monte-carlo/01_mcmc/04_gibbs-sampling.mp4 29.32 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/03_applications-and-examples/01_general-em-for-gmm.mp4 29.47 MB
2. competitive-data-science/05_validation/01_validation/04_data-splitting-strategies.mp4 30.05 MB
3. bayesian-methods-in-machine-learning/02_expectation-maximization-algorithm/02_expectation-maximization-algorithm/03_e-step-details.mp4 30.4 MB
3. bayesian-methods-in-machine-learning/06_gaussian-processes-bayesian-optimization/01_gaussian-processes-and-bayesian-optimization/04_derivation-of-main-formula.mp4 31.09 MB
1. intro-to-deep-learning/03_deep-learning-for-images/02_modern-cnns/01_training-tips-and-tricks-for-deep-cnns.mp4 31.33 MB
2. competitive-data-science/09_hyperparameter-optimization/02_tips-and-tricks/01_practical-guide.mp4 32.82 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/02_latent-dirichlet-allocation/04_lda-e-step-theta.mp4 33.36 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/01_variational-inference/03_example-ising-model.mp4 33.5 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/01_variational-inference/02_mean-field-approximation.mp4 35.44 MB
2. competitive-data-science/12_competitions-go-through/01_competitions-go-through/04_microsoft-malware-classification-challenge.mp4 37.84 MB
2. competitive-data-science/05_validation/01_validation/05_problems-occurring-during-validation.mp4 39.49 MB
2. competitive-data-science/07_metrics-optimization/01_metrics-optimization/05_classification-metrics-review.mp4 39.59 MB
3. bayesian-methods-in-machine-learning/03_variational-inference-latent-dirichlet-allocation/02_latent-dirichlet-allocation/06_lda-m-step-prediction.mp4 40.57 MB
其他位置