1.03 GB | 00:36:28 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
01 introduction.mp4 (20.23 MB)
04 what-is-machine-learning.mp4 (23.59 MB)
05 the-machine-learning-workflow.mp4 (43.64 MB)
06 our-first-model-nhl-game-outcomes.mp4 (60.28 MB)
07 building-the-logistic-regression-model.mp4 (19.06 MB)
08 considerations-in-deploying-the-model.mp4 (57.3 MB)
09 wrap-up.mp4 (5.18 MB)
01 introduction-to-support-vector-machines-svms.mp4 (56.13 MB)
02 polynomial-support-vector-machines.mp4 (46.67 MB)
03 cross-validation.mp4 (45.27 MB)
04 a-real-world-svm-model-boxing-punch-classification.mp4 (67.19 MB)
01 decision-trees.mp4 (36.43 MB)
02 a-multiclass-tree-approach.mp4 (24.81 MB)
03 model-trees.mp4 (62.11 MB)
04 tuning-and-inspecting-model-trees.mp4 (37.29 MB)
01 ensembles.mp4 (99.65 MB)
02 additional-machine-learning-concepts.mp4 (24.91 MB)
03 baseball-hall-of-fame-prediction.mp4 (68.81 MB)
04 baseball-hall-of-fame-demonstration-part-1.mp4 (88.81 MB)
05 baseball-hall-of-fame-demonstration-part-2.mp4 (164.68 MB)]
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