7.06 GB | 1h 6min 40s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
1 Introduction.mp4 (197.28 MB)
2 Setup of the Anaconda Cloud Notebook.mp4 (108.45 MB)
3 Download and installation of the Anaconda Distribution (optional).mp4 (158.62 MB)
4 The Conda Package Management System (optional).mp4 (268.34 MB)
1 Regression, Prediction, and Supervised Learning Section Overview (I).mp4 (121.78 MB)
2 The Traditional Simple Regression Model (II).mp4 (173.57 MB)
3 The Traditional Simple Regression Model (III).mp4 (317.52 MB)
4 Some practical and useful modelling concepts (IV).mp4 (114.68 MB)
5 Some practical and useful modelling concepts (V).mp4 (120.23 MB)
6 Linear Multiple Regression model (VI).mp4 (338.27 MB)
7 Linear Multiple Regression model (VII).mp4 (233.02 MB)
8 Multivariate Polynomial Multiple Regression models (VIII).mp4 (99.67 MB)
9 Multivariate Polynomial Multiple Regression models (VIIII).mp4 (408.81 MB)
10 Regression Regularization, Lasso and Ridge models (X).mp4 (520.41 MB)
11 Decision Tree Regression models (XI).mp4 (476.1 MB)
12 Random Forest Regression (XII).mp4 (410.58 MB)
13 Voting Regression (XIII).mp4 (244.89 MB)
1 Classification and Supervised Learning, overview.mp4 (118.28 MB)
2 Logistic Regression Classifier.mp4 (379.64 MB)
3 The Naive Bayes Classifier.mp4 (328.28 MB)
4 The Decision Tree Classifier.mp4 (549.08 MB)
5 The Random Forest Classifier.mp4 (331.52 MB)
6 The Voting Classifier.mp4 (203.93 MB)
1 Cluster Analysis, an overview.mp4 (202.21 MB)
2 K-Means Cluster Analysis, and an introduction to auto-updated K-means algorithms.mp4 (253.7 MB)
3 Density-Based Spatial Clustering of Applications with Noise (DBSCAN).mp4 (334.38 MB)
4 Four Hierarchical Clustering algorithms.mp4 (210.64 MB)]
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