466.26 MB | 00:04:05 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
01 introduction-to-the-course.mp4 (45.61 MB)
02 introduction-to-problem-statement.mp4 (6.07 MB)
03 division-of-the-dataset.mp4 (7.42 MB)
02 overfitting-and-underfitting.mp4 (11.55 MB)
03 introduction-to-the-apex-dataset.mp4 (6.68 MB)
04 l1-regularization.mp4 (14.37 MB)
05 l2-regularization.mp4 (12.6 MB)
06 elastic-net-regularization.mp4 (14.63 MB)
01 fine-tuning-logistic-regression.mp4 (6.16 MB)
02 l1-regularization.mp4 (18.6 MB)
03 l2-regularization.mp4 (5.62 MB)
04 elastic-net-regularization.mp4 (11.99 MB)
02 understanding-ensemble-learning.mp4 (9.58 MB)
03 introducing-bagging-algorithms.mp4 (6.57 MB)
04 hands-on-to-bagging-meta-estimator.mp4 (13.38 MB)
05 introduction-to-random-forest.mp4 (9.69 MB)
06 understanding-out-of-bag-score.mp4 (7.14 MB)
07 random-forest-vs-classical-bagging-vs-decision-tree.mp4 (7.65 MB)
02 introduction-to-boosting.mp4 (10.24 MB)
03 adaboost-step-by-step-explanation.mp4 (11.63 MB)
04 hands-on-adaboost.mp4 (8.22 MB)
05 gradient-boosting-machines-gbm.mp4 (5.73 MB)
06 hands-on-gradient-boost.mp4 (4.8 MB)
07 other-algo-xgboost-lightboost-catboost.mp4 (17.11 MB)
01 introduction-to-feature-engineering-and-hyperparameter-tuning.mp4 (5.66 MB)
02 spliting-the-dataset.mp4 (3.18 MB)
03 feature-transformation.mp4 (12.08 MB)
04 feature-generation.mp4 (16.35 MB)
05 feature-seletion.mp4 (16.78 MB)
01 introduction-to-hyperparameter-and-grid-search-cv.mp4 (6.41 MB)
02 grid-search-cv.mp4 (11.54 MB)
03 random-search-cv.mp4 (7.01 MB)
04 bayesan-optimization.mp4 (5.79 MB)
05 bayesian-optimization-in-synergix-dataset.mp4 (8.54 MB)
02 introduction-to-the-module.mp4 (7.5 MB)
03 understanding-voting.mp4 (5.92 MB)
04 leveraging-the-voting.mp4 (8.55 MB)
05 understanding-stacking-ensemble-learning.mp4 (13 MB)
06 understanding-hold-out-method-blending.mp4 (9.74 MB)
01 the-stepping-stones-in-model-selection.mp4 (14.34 MB)
02 factors-to-consider-while-selecting-a-model.mp4 (11.48 MB)
02 introduction-to-problem-statement.mp4 (6.07 MB)
03 division-of-the-dataset.mp4 (7.42 MB)
02 overfitting-and-underfitting.mp4 (11.55 MB)
03 introduction-to-the-apex-dataset.mp4 (6.68 MB)
04 l1-regularization.mp4 (14.37 MB)
05 l2-regularization.mp4 (12.6 MB)
06 elastic-net-regularization.mp4 (14.63 MB)
01 fine-tuning-logistic-regression.mp4 (6.16 MB)
02 l1-regularization.mp4 (18.6 MB)
03 l2-regularization.mp4 (5.62 MB)
04 elastic-net-regularization.mp4 (11.99 MB)
02 understanding-ensemble-learning.mp4 (9.58 MB)
03 introducing-bagging-algorithms.mp4 (6.57 MB)
04 hands-on-to-bagging-meta-estimator.mp4 (13.38 MB)
05 introduction-to-random-forest.mp4 (9.69 MB)
06 understanding-out-of-bag-score.mp4 (7.14 MB)
07 random-forest-vs-classical-bagging-vs-decision-tree.mp4 (7.65 MB)
02 introduction-to-boosting.mp4 (10.24 MB)
03 adaboost-step-by-step-explanation.mp4 (11.63 MB)
04 hands-on-adaboost.mp4 (8.22 MB)
05 gradient-boosting-machines-gbm.mp4 (5.73 MB)
06 hands-on-gradient-boost.mp4 (4.8 MB)
07 other-algo-xgboost-lightboost-catboost.mp4 (17.11 MB)
01 introduction-to-feature-engineering-and-hyperparameter-tuning.mp4 (5.66 MB)
02 spliting-the-dataset.mp4 (3.18 MB)
03 feature-transformation.mp4 (12.08 MB)
04 feature-generation.mp4 (16.35 MB)
05 feature-seletion.mp4 (16.78 MB)
01 introduction-to-hyperparameter-and-grid-search-cv.mp4 (6.41 MB)
02 grid-search-cv.mp4 (11.54 MB)
03 random-search-cv.mp4 (7.01 MB)
04 bayesan-optimization.mp4 (5.79 MB)
05 bayesian-optimization-in-synergix-dataset.mp4 (8.54 MB)
02 introduction-to-the-module.mp4 (7.5 MB)
03 understanding-voting.mp4 (5.92 MB)
04 leveraging-the-voting.mp4 (8.55 MB)
05 understanding-stacking-ensemble-learning.mp4 (13 MB)
06 understanding-hold-out-method-blending.mp4 (9.74 MB)
01 the-stepping-stones-in-model-selection.mp4 (14.34 MB)
02 factors-to-consider-while-selecting-a-model.mp4 (11.48 MB)
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