Tutorials > Foundations of Machine Learning
Foundations of Machine LearningDate: 23 March 2025 | Posted by: AD-TEAM |
![]() 744.12 MB | 00:12:00 | mp4 | 1280X720 | 16:9 Genre:eLearning |Language:English Files Included : 01 gateway-to-the-course.mp4 (17.43 MB) 02 course-and-instructor-introduction-video.mp4 (8.99 MB) 01 introduction-to-problem-statement.mp4 (11.23 MB) 03 how-do-we-make-predictions.mp4 (4.22 MB) 04 methodology-of-evaluating-predictions.mp4 (5.49 MB) 05 introduction-to-data-division.mp4 (4.77 MB) 06 building-benchmark-models-and-evaluating-it.mp4 (10.24 MB) 06 building-benchmark-models-and-evaluating-it Benchmark Model.zip (82.2 KB) 07 introduction-to-machine-learning.mp4 (7.94 MB) 08 applications-of-machine-learning.mp4 (8.9 MB) 09 types-of-machine-learning.mp4 (7.94 MB) 01 ml-workflow.mp4 (18.13 MB) 02 tasks-to-be-performed.mp4 (12.03 MB) 02 tasks-to-be-performed Data Preprocessing.zip (5.65 MB) 03 combining-product-attribute-data-with-pos-data.mp4 (16.5 MB) 04 combining-all-the-tables-in-the-dataframe.mp4 (18.1 MB) 05 understanding-the-combined-data.mp4 (7.51 MB) 06 treating-missing-values-part-1.mp4 (12.14 MB) 07 treating-missing-values-part-2.mp4 (8.36 MB) 08 outlier-detection-and-treatment.mp4 (5.07 MB) 09 preparing-the-dataset-for-supervised-and-unsupervised-models.mp4 (8.1 MB) 10 generative-ai-for-data-analysis.mp4 (15.71 MB) 01 introduction-to-knn.mp4 (3.7 MB) 02 building-a-knn-model.mp4 (5 MB) 03 choosing-the-optimal-k.mp4 (3.05 MB) 04 different-ways-to-calculate-distance.mp4 (9.6 MB) 05 problems-with-distance-based-algorithm.mp4 (5.54 MB) 01 sklearn-to-build-optimal-process-to-build-an-ml-model.mp4 (6.32 MB) 02 building-a-knn-classification-model-and-evaluating-it.mp4 (22.36 MB) 02 building-a-knn-classification-model-and-evaluating-it KNN Model for Synergix.zip (959.33 KB) 03 choosing-the-right-k-value.mp4 (3.46 MB) 04 bias-and-variance.mp4 (9.34 MB) 01 understanding-confusion-matrix-and-accuracy.mp4 (12.64 MB) 01 understanding-confusion-matrix-and-accuracy Classification Evalauation Metrics - Notebook Dataset.zip (917.55 KB) 02 a-deep-dive-into-precision-recall-and-f1-score.mp4 (14.16 MB) 03 understanding-the-au-roc-curve.mp4 (8.64 MB) 01 why-do-we-calculate-rmse.mp4 (9.8 MB) 01 why-do-we-calculate-rmse Evaluation Metrics for Regression Problems.zip (878.68 KB) 02 understanding-r2-score-and-adjusted-r2-score.mp4 (8.68 MB) 01 train-test-split.mp4 (14.63 MB) 02 train-test-split-ratio-and-limit.mp4 (4.96 MB) 03 cross-validation.mp4 (6.47 MB) 04 implementing-cross-validation.mp4 (9.97 MB) 04 implementing-cross-validation Data Division Resorces.zip (833.58 KB) 05 benchmark-models.mp4 (11.15 MB) 01 introduction-to-linear-regression.mp4 (8.11 MB) 02 significance-of-slope-and-intercept-in-the-linear-regression.mp4 (14.92 MB) 02 significance-of-slope-and-intercept-in-the-linear-regression Linear Regression Notebooks.zip (301.99 KB) 03 how-model-decides-the-best-fit-line.mp4 (7.69 MB) 04 lets-build-a-simple-linear-regression-model.mp4 (9.59 MB) 05 model-understanding-using-descriptive-approach.mp4 (18.04 MB) 06 model-understanding-using-descriptive-approach-ii.mp4 (15.51 MB) 07 model-building-using-predictive-approach.mp4 (8.45 MB) 01 introduction.mp4 (3.05 MB) 02 lines-to-curves-with-logistic-regression.mp4 (7.32 MB) 02 lines-to-curves-with-logistic-regression Logistic Regression Notebook.zip (15.88 KB) 03 reading-between-the-curves-with-log-loss.mp4 (9.77 MB) 04 stats-model-summary.mp4 (11.28 MB) 05 feature-selection-and-scaling.mp4 (11.18 MB) 06 predictive-model-in-logistic-regression.mp4 (7.34 MB) 01 introduction-to-decision-trees.mp4 (9.34 MB) 02 lets-visualize-the-decision-tree.mp4 (12.71 MB) 02 lets-visualize-the-decision-tree Visualizing Decision Trees.rar (223.92 KB) 03 how-do-decision-trees-decide.mp4 (12.64 MB) 04 how-decision-trees-make-predictions.mp4 (5.53 MB) 05 hands-on-building-the-decision-tree-classification-model.mp4 (21.37 MB) 05 hands-on-building-the-decision-tree-classification-model Decision Tree - Classification.rar (634.58 KB) 06 hyperparameters-of-decision-trees.mp4 (9.56 MB) 07 hands-on-building-the-decision-tree-classification-model-part-2.mp4 (5.01 MB) 08 building-a-decision-tree-regression-model.mp4 (9.5 MB) 08 building-a-decision-tree-regression-model Decision Tree - Regression.rar (632.18 KB) 09 handling-imbalanced-datasets.mp4 (10.65 MB) 10 handling-imbalanced-datasets-hands-on.mp4 (14.92 MB) 10 handling-imbalanced-datasets-hands-on Handling Imbalanced Datasets.rar (631.84 KB) 01 setting-the-context.mp4 (7.39 MB) 02 choosing-clustering-algorithms.mp4 (9.27 MB) 03 solving-our-problem-using-k-means-part-1.mp4 (18.5 MB) 03 solving-our-problem-using-k-means-part-1 K-means Clustering for Synergix.rar (1 MB) 04 solving-our-problem-using-k-means-part-2.mp4 (6.47 MB) 05 finding-optimal-k-value.mp4 (12.62 MB) 06 analysis-and-insights-based-on-the-plot.mp4 (5.23 MB) 01 introduction-to-hierarchical-clustering-analysis-hca.mp4 (5.77 MB) 02 solving-our-problem-using-hierarchical-clustering.mp4 (10.1 MB) 02 solving-our-problem-using-hierarchical-clustering Hierarchical Clustering Analysis for Synergix.rar (855.97 KB) 03 introduction-to-dbscan.mp4 (12.17 MB) 04 solving-our-problem-using-dbscan-clustering.mp4 (10.32 MB) 04 solving-our-problem-using-dbscan-clustering DBSCAN Clustering for Synergix.rar (785.65 KB) 06 course-summary.mp4 (8.33 MB)] Screenshot ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() See full article |