Edureka Applied Machine Learning With Python 2025

[0dayddl]

3.52 GB | 00:07:16 | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

02-course introduction.mp4 (24.37 MB)
03-machine learning in industry.mp4 (25.94 MB)
04-how companies use machine learning.mp4 (31.63 MB)
01-machine learning process.mp4 (22.34 MB)
02-steps in machine learning.mp4 (23.02 MB)
03-types of machine learning.mp4 (37.02 MB)
01-introduction to linear regression.mp4 (32.88 MB)
02-real life examples.mp4 (44.56 MB)
03-calculating ols.mp4 (75.45 MB)
04-equation of ols.mp4 (30.86 MB)
05-assumptions in linear regression.mp4 (41.51 MB)
06-demonstration setting up the model.mp4 (40.62 MB)
07-calculating r square and rmse.mp4 (51.03 MB)
08-residual plot and q q plot.mp4 (17.28 MB)
09-cooks distance.mp4 (40.38 MB)
10-real life examples of logistic regression.mp4 (41.2 MB)
11-what is logistic regression.mp4 (49.63 MB)
12-cost function.mp4 (27.61 MB)
13-assumptions in logistic regression.mp4 (35.82 MB)
14-demonstration of logistic regression transforming data.mp4 (57.32 MB)
15-demonstration of logistic regression developing the model.mp4 (32.73 MB)
01-confusion matrix.mp4 (19.33 MB)
02-example for calculating confusion matrix.mp4 (58.54 MB)
03-conditions for over fitting and under fitting.mp4 (22.1 MB)
04-overfitting and underfitting.mp4 (57.48 MB)
05-performance metrics mse rmse mae mape.mp4 (47.02 MB)
06-r square rmsle and adjusted r square.mp4 (33.11 MB)
07-working of r square.mp4 (42.07 MB)
08-significance of r square.mp4 (52.8 MB)
01-summary for inception of machine learning.mp4 (16 MB)
01-classification in machine learning.mp4 (31.06 MB)
02-what is decision tree.mp4 (63.62 MB)
03-decision tree entropy and information gain.mp4 (53.33 MB)
04-step by step building of decision tree.mp4 (77.84 MB)
05-pruning in decision tree.mp4 (53.45 MB)
06-demonstration importing data.mp4 (46.62 MB)
07-demonstration building decision tree and random forest.mp4 (63.65 MB)
08-demonstration importance of features.mp4 (25.33 MB)
09-demonstration production ready random forest.mp4 (18.78 MB)
10-demonstration hyperparameter tuning.mp4 (31.25 MB)
01-what is svm.mp4 (37.05 MB)
02-terminologies in svm.mp4 (86.16 MB)
03-hinge loss function and other parameters.mp4 (82.78 MB)
04-demonstration of svm exploring the data.mp4 (29.44 MB)
05-demonstration of svm setting up the svm classifier.mp4 (67.99 MB)
06-what is naive bayes.mp4 (18.8 MB)
07-working of naive bayes bayes theorem.mp4 (46.3 MB)
08-example of naive bayes algorithm.mp4 (74.88 MB)
09-demonstration of naive bayes code.mp4 (36.34 MB)
10-working of knn.mp4 (32.92 MB)
11-example of knn algorithm.mp4 (45.24 MB)
12-demonstration of knn setting up the model.mp4 (50.31 MB)
13-demonstration of knn transforming and scaling data.mp4 (46.89 MB)
14-demonstration of knn creating classifier.mp4 (28.13 MB)
01-dimensionality reduction.mp4 (57.45 MB)
02-introduction to pca.mp4 (53.44 MB)
03-applying pca.mp4 (45.33 MB)
04-eigen values and eigen vectors.mp4 (59.38 MB)
05-demonstration initializing pca.mp4 (25.12 MB)
06-demonstration determining optimal number of components through pca.mp4 (36.68 MB)
07-demonstration implementing optimal pca.mp4 (45.11 MB)
08-working of lda.mp4 (55.51 MB)
09-demonstration of lda.mp4 (58.53 MB)
01-summary for machine learning algorithms.mp4 (16.4 MB)
01-what are association rules.mp4 (45.32 MB)
02-apriori algorithm.mp4 (34.39 MB)
03-demonstrating apriori algorithm.mp4 (87.65 MB)
01-what are recommendation engine.mp4 (34.48 MB)
02-cbf.mp4 (33.58 MB)
03-demonstration of recommendation engine preparing data.mp4 (56.71 MB)
04-demonstration testing the model.mp4 (49.46 MB)
01-elements for reinforcement learning.mp4 (26.98 MB)
02-demonstration of boosting explaining the dataset.mp4 (55.03 MB)
03-demonstration of boosting cleaning and transforming dataset.mp4 (56.3 MB)
04-demonstration of boosting factors affecting promotion.mp4 (34.52 MB)
05-demonstration of boosting total score and service affecting promotion.mp4 (48.38 MB)
07-demonstration of boosting department influencing promotion.mp4 (49.06 MB)
09-demonstration of boosting modeling the data.mp4 (42.37 MB)
10-demonstration of boosting building a model.mp4 (73.19 MB)
11-working of k means algorithm.mp4 (32.98 MB)
12-demonstration of k means clustering.mp4 (61.1 MB)
01-summary for association rule mining and recommendation system.mp4 (22.79 MB)
01-course summary for applied machine learning with python.mp4 (19.28 MB)

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[0dayddl]

2 GB | 00:07:16 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

02 course-introduction.mp4 (14.8 MB)
03 machine-learning-in-industry.mp4 (15.59 MB)
04 how-companies-use-machine-learning.mp4 (18.89 MB)
01 machine-learning-process.mp4 (14.84 MB)
02 steps-in-machine-learning.mp4 (13.79 MB)
03 types-of-machine-learning.mp4 (21.81 MB)
01 introduction-to-linear-regression.mp4 (18.61 MB)
02 real-life-examples.mp4 (22.05 MB)
03 calculating-ols.mp4 (40.38 MB)
04 equation-of-ols.mp4 (16.29 MB)
05 assumptions-in-linear-regression.mp4 (22.41 MB)
06 demonstration-setting-up-the-model.mp4 (23.13 MB)
07 calculating-r-square-and-rmse.mp4 (28.36 MB)
08 residual-plot-and-q-q-plot.mp4 (9.96 MB)
09 cooks-distance.mp4 (22.59 MB)
10 real-life-examples-of-logistic-regression.mp4 (21.03 MB)
11 what-is-logistic-regression.mp4 (26.84 MB)
12 cost-function.mp4 (13.93 MB)
13 assumptions-in-logistic-regression.mp4 (19.09 MB)
14 demonstration-of-logistic-regression-transforming-data.mp4 (29.9 MB)
15 demonstration-of-logistic-regression-developing-the-model.mp4 (18.35 MB)
01 confusion-matrix.mp4 (12.22 MB)
02 example-for-calculating-confusion-matrix.mp4 (32.97 MB)
03 conditions-for-over-fitting-and-under-fitting.mp4 (14.45 MB)
04 overfitting-and-underfitting.mp4 (30.5 MB)
05 performance-metrics-mse-rmse-mae-mape.mp4 (26.41 MB)
06 r-square-rmsle-and-adjusted-r-square.mp4 (19.11 MB)
07 working-of-r-square.mp4 (23.97 MB)
08 significance-of-r-square.mp4 (29.25 MB)
01 summary-for-inception-of-machine-learning.mp4 (9.74 MB)
01 classification-in-machine-learning.mp4 (19.62 MB)
02 what-is-decision-tree.mp4 (32.56 MB)
03 decision-tree-entropy-and-information-gain.mp4 (29.62 MB)
04 step-by-step-building-of-decision-tree.mp4 (38.71 MB)
05 pruning-in-decision-tree.mp4 (26.68 MB)
06 demonstration-importing-data.mp4 (26.8 MB)
07 demonstration-building-decision-tree-and-random-forest.mp4 (34.49 MB)
08 demonstration-importance-of-features.mp4 (14.1 MB)
09 demonstration-production-ready-random-forest.mp4 (10.99 MB)
10 demonstration-hyperparameter-tuning.mp4 (17.72 MB)
01 what-is-svm.mp4 (20.1 MB)
02 terminologies-in-svm.mp4 (42.91 MB)
03 hinge-loss-function-and-other-parameters.mp4 (43.01 MB)
04 demonstration-of-svm-exploring-the-data.mp4 (17.08 MB)
05 demonstration-of-svm-setting-up-the-svm-classifier.mp4 (36.63 MB)
06 what-is-naive-bayes.mp4 (11.9 MB)
07 working-of-naive-bayes-bayes-theorem.mp4 (23.17 MB)
08 example-of-naive-bayes-algorithm.mp4 (37.67 MB)
09 demonstration-of-naive-bayes-code.mp4 (21.04 MB)
10 working-of-knn.mp4 (17.86 MB)
11 example-of-knn-algorithm.mp4 (23.3 MB)
12 demonstration-of-knn-setting-up-the-model.mp4 (28.2 MB)
13 demonstration-of-knn-transforming-and-scaling-data.mp4 (25.26 MB)
14 demonstration-of-knn-creating-classifier.mp4 (15.24 MB)
01 dimensionality-reduction.mp4 (31.58 MB)
02 introduction-to-pca.mp4 (27.97 MB)
03 applying-pca.mp4 (23.87 MB)
04 eigen-values-and-eigen-vectors.mp4 (29.48 MB)
05 demonstration-initializing-pca.mp4 (13.78 MB)
06 demonstration-determining-optimal-number-of-components-through-pca.mp4 (21.36 MB)
07 demonstration-implementing-optimal-pca.mp4 (25.04 MB)
08 working-of-lda.mp4 (29.56 MB)
09 demonstration-of-lda.mp4 (32.12 MB)
01 summary-for-machine-learning-algorithms.mp4 (10.05 MB)
01 what-are-association-rules.mp4 (27.58 MB)
02 apriori-algorithm.mp4 (20.99 MB)
03 demonstrating-apriori-algorithm.mp4 (48.01 MB)
01 what-are-recommendation-engine.mp4 (22.26 MB)
02 cbf.mp4 (21.73 MB)
03 demonstration-of-recommendation-engine-preparing-data.mp4 (31.67 MB)
04 demonstration-testing-the-model.mp4 (27.23 MB)
01 elements-for-reinforcement-learning.mp4 (18.28 MB)
02 demonstration-of-boosting-explaining-the-dataset.mp4 (30.47 MB)
03 demonstration-of-boosting-cleaning-and-transforming-dataset.mp4 (30.94 MB)
04 demonstration-of-boosting-factors-affecting-promotion.mp4 (19.8 MB)
05 demonstration-of-boosting-total-score-and-service-affecting-promotion.mp4 (27.04 MB)
06 demonstration-of-boosting-age-previous-year-rating-influencing-promotion.mp4 (17.78 MB)
07 demonstration-of-boosting-department-influencing-promotion.mp4 (26.9 MB)
08 demonstration-of-boosting-education-affecting-promotion-and-summarization.mp4 (27.49 MB)
09 demonstration-of-boosting-modeling-the-data.mp4 (24.15 MB)
10 demonstration-of-boosting-building-a-model.mp4 (42.34 MB)
11 working-of-k-means-algorithm.mp4 (20.23 MB)
12 demonstration-of-k-means-clustering.mp4 (34.22 MB)
01 summary-for-association-rule-mining-and-recommendation-system.mp4 (13.5 MB)
01 course-summary-for-applied-machine-learning-with-python.mp4 (11.91 MB)

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