971.99 MB | 00:41:42 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
01 welcome-to-machine-learning (22.33 MB)
02 applications-of-machine-learning (34.18 MB)
01 what-is-machine-learning (26.38 MB)
02 supervised-learning-part-1 (13.06 MB)
03 supervised-learning-part-2 (13.7 MB)
04 unsupervised-learning-part-1 (17.85 MB)
05 unsupervised-learning-part-2 (7.76 MB)
06 jupyter-notebooks (20.15 MB)
01 linear-regression-model-part-1 (18.98 MB)
02 linear-regression-model-part-2 (15.55 MB)
03 cost-function-formula (15.64 MB)
04 cost-function-intuition (27.74 MB)
05 visualizing-the-cost-function (17.07 MB)
06 visualization-examples (17.07 MB)
01 gradient-descent (20.63 MB)
02 implementing-gradient-descent (19.57 MB)
03 gradient-descent-intuition (12.41 MB)
04 learning-rate (15.97 MB)
05 gradient-descent-for-linear-regression (15.58 MB)
06 running-gradient-descent (17.79 MB)
01 multiple-features (17.52 MB)
02 vectorization-part-1 (16.17 MB)
03 vectorization-part-2 (16.67 MB)
04 gradient-descent-for-multiple-linear-regression (18.54 MB)
01 feature-scaling-part-1 (12.83 MB)
02 feature-scaling-part-2 (13.6 MB)
03 checking-gradient-descent-for-convergence (10.23 MB)
04 choosing-the-learning-rate (15.85 MB)
05 feature-engineering (7.57 MB)
06 polynomial-regression (22.5 MB)
01 motivations (19.96 MB)
02 logistic-regression (20.32 MB)
03 decision-boundary (17.7 MB)
01 cost-function-for-logistic-regression (23.36 MB)
02 simplified-cost-function-for-logistic-regression (10.98 MB)
01 gradient-descent-implementation (11.93 MB)
01 the-problem-of-overfitting (22.14 MB)
02 addressing-overfitting (14.92 MB)
03 cost-function-with-regularization (15.88 MB)
04 regularized-linear-regression (18.61 MB)
05 regularized-logistic-regression (20.55 MB)
01 andrew-ng-and-fei-fei-li-on-human-centered-ai (235.87 MB)
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