Python Data Science Unsupervised Machine Learning

Files Included :
1 -Course Introduction.mp4 (48.09 MB)
2 -About This Series.mp4 (4.43 MB)
3 -Course Structure & Outline.mp4 (20.72 MB)
4 -Data Science in Python - Unsupervised Learning.zip (12.98 MB)
4 -Introducing the Course Project.mp4 (5.94 MB)
5 -Setting Expectations.mp4 (10.01 MB)
6 -Jupyter Installation & Launch.mp4 (37.97 MB)
1 -Project Overview.mp4 (11.88 MB)
2 -SOLUTION Data Prep.mp4 (17.11 MB)
3 -SOLUTION TruncatedSVD.mp4 (98.4 MB)
4 -SOLUTION Cosine Similarity.mp4 (40.58 MB)
5 -SOLUTION Recommendations.mp4 (30.23 MB)
1 -Section Introduction.mp4 (5.27 MB)
2 -Unsupervised Learning Flow Chart.mp4 (16.7 MB)
3 -Unsupervised Learning Techniques & Applications.mp4 (25.9 MB)
4 -Unsupervised Learning in the Data Science Workflow.mp4 (17.3 MB)
5 -Key Takeaways.mp4 (14.71 MB)
1 -Final Project Overview.mp4 (14.8 MB)
2 -SOLUTION Data Prep & EDA.mp4 (82.04 MB)
3 -SOLUTION Clustering.mp4 (30.35 MB)
4 -SOLUTION PCA.mp4 (29.98 MB)
5 -SOLUTION Clustering (Round 2).mp4 (26.15 MB)
6 -SOLUTION PCA (Round 2).mp4 (38.69 MB)
7 -SOLUTION EDA on Clusters.mp4 (30.68 MB)
8 -SOLUTION Recommendations.mp4 (14.53 MB)
1 -Section Introduction.mp4 (4.82 MB)
10 -Step 4 Exploring Data.mp4 (6.34 MB)
11 -Step 5 Modeling Data.mp4 (8.24 MB)
12 -Step 6 Sharing Insights.mp4 (7.47 MB)
13 -Unsupervised Learning.mp4 (4.53 MB)
14 -Key Takeaways.mp4 (9.89 MB)
2 -What is Data Science.mp4 (4.65 MB)
3 -Data Science Skill Set.mp4 (9.38 MB)
4 -What is Machine Learning.mp4 (9.57 MB)
5 -Common Machine Learning Algorithms.mp4 (16.46 MB)
6 -Data Science Workflow.mp4 (5.59 MB)
7 -Step 1 Scoping a Project.mp4 (6.88 MB)
8 -Step 2 Gathering Data.mp4 (5.64 MB)
9 -Step 3 Cleaning Data.mp4 (7.65 MB)
1 -Section Introduction.mp4 (3.45 MB)
2 -Unsupervised Learning 101.mp4 (21.34 MB)
3 -Unsupervised Learning Techniques.mp4 (18.09 MB)
4 -Unsupervised Learning Applications.mp4 (10.36 MB)
5 -Structure of This Course.mp4 (7.45 MB)
6 -Unsupervised Learning Workflow.mp4 (26.26 MB)
7 -Key Takeaways.mp4 (10.37 MB)
1 -Section Introduction.mp4 (6.41 MB)
10 -Handling Missing Data.mp4 (50.53 MB)
11 -Converting to Numeric.mp4 (45.76 MB)
12 -Converting to DateTime.mp4 (47.35 MB)
13 -Extracting DateTime.mp4 (31.93 MB)
14 -Calculating Based on a Condition.mp4 (21.05 MB)
15 -Dummy Variables.mp4 (29.91 MB)
16 -ASSIGNMENT Preparing Columns for Modeling.mp4 (4.89 MB)
17 -SOLUTION Preparing Columns for Modeling.mp4 (16.85 MB)
18 -Feature Engineering.mp4 (16.09 MB)
19 -Feature Engineering During Data Prep.mp4 (11.41 MB)
2 -Data Prep for Unsupervised Learning.mp4 (11.32 MB)
20 -Applying Calculations.mp4 (27.59 MB)
21 -Binning Values.mp4 (18.96 MB)
22 -Identifying Proxy Variables.mp4 (30.58 MB)
23 -Feature Engineering Tips.mp4 (8.3 MB)
24 -ASSIGNMENT Feature Engineering.mp4 (3.83 MB)
25 -SOLUTION Feature Engineering.mp4 (12.27 MB)
26 -Excluding Identifiers From Modeling.mp4 (12.86 MB)
27 -Feature Selection.mp4 (25.83 MB)
28 -ASSIGNMENT Feature Selection.mp4 (3.61 MB)
29 -SOLUTION Feature Selection.mp4 (18.26 MB)
3 -Setting the Correct Row Granularity.mp4 (31.96 MB)
30 -Feature Scaling.mp4 (9.21 MB)
31 -Normalization.mp4 (43.64 MB)
32 -Standardization.mp4 (35.44 MB)
33 -ASSIGNMENT Feature Scaling.mp4 (3.39 MB)
34 -SOLUTION Feature Scaling.mp4 (20.82 MB)
35 -Key Takeaways.mp4 (10.14 MB)
4 -DEMO Group By.mp4 (30.68 MB)
5 -DEMO Pivot.mp4 (21.41 MB)
6 -ASSIGNMENT Setting the Correct Row Granularity.mp4 (12.68 MB)
7 -SOLUTION Setting the Correct Row Granularity.mp4 (32.33 MB)
8 -Preparing Columns for Modeling.mp4 (10.24 MB)
9 -Identifying Missing Data.mp4 (36.6 MB)
1 -Section Introduction.mp4 (5.61 MB)
10 -SOLUTION K-Means Clustering.mp4 (44.38 MB)
11 -Inertia.mp4 (23.73 MB)
12 -Plotting Inertia in Python.mp4 (15.83 MB)
13 -DEMO Plotting Inertia in Python.mp4 (58.67 MB)
14 -ASSIGNMENT Inertia Plot.mp4 (5.82 MB)
15 -SOLUTION Inertia Plot.mp4 (42.35 MB)
16 -Tuning a K-Means Model.mp4 (24.05 MB)
17 -DEMO Tuning a K-Means Model.mp4 (49.79 MB)
18 -ASSIGNMENT Tuning a K-Means Model.mp4 (5.8 MB)
19 -SOLUTION Tuning a K-Means Model.mp4 (78.59 MB)
2 -Clustering Basics.mp4 (18.67 MB)
20 -Selecting the Best Model.mp4 (35.96 MB)
21 -DEMO Selecting the Best Model.mp4 (81.04 MB)
22 -ASSIGNMENT Selecting the Best K-Means Model.mp4 (7.78 MB)
23 -SOLUTION Selecting the Best K-Means Model.mp4 (111.95 MB)
24 -Hierarchical Clustering.mp4 (54.16 MB)
25 -Dendrograms in Python.mp4 (75.44 MB)
26 -Agglomerative Clustering in Python.mp4 (22.48 MB)
27 -DEMO Agglomerative Clustering in Python.mp4 (39.67 MB)
28 -Cluster Maps in Python.mp4 (16.19 MB)
29 -DEMO Cluster Maps in Python.mp4 (92.49 MB)
3 -K-Means Clustering.mp4 (28.57 MB)
30 -ASSIGNMENT Hierarchical Clustering.mp4 (8.88 MB)
31 -SOLUTION Hierarchical Clustering.mp4 (53.87 MB)
32 -DBSCAN.mp4 (41.56 MB)
33 -DBSCAN in Python.mp4 (23.42 MB)
34 -Silhouette Score.mp4 (27.53 MB)
35 -Silhouette Score in Python.mp4 (9.18 MB)
36 -DEMO DBSCAN and Silhouette Score in Python.mp4 (140.94 MB)
37 -ASSIGNMENT DBSCAN.mp4 (5.94 MB)
38 -SOLUTION DBSCAN.mp4 (37.39 MB)
39 -Comparing Clustering Algorithms.mp4 (46.11 MB)
4 -K-Means Clustering in Python.mp4 (39.17 MB)
40 -Clustering Next Steps.mp4 (21.49 MB)
41 -DEMO Compare Clustering Models.mp4 (25.25 MB)
42 -DEMO Label Unseen Data.mp4 (104.51 MB)
43 -Key Takeaways.mp4 (10.71 MB)
5 -DEMO K-Means Clustering in Python.mp4 (47.33 MB)
6 -Visualizing K-Means Clustering.mp4 (56.6 MB)
7 -Interpreting K-Means Clustering.mp4 (33.86 MB)
8 -Visualizing Cluster Centers.mp4 (48.06 MB)
9 -ASSIGNMENT K-Means Clustering.mp4 (7.4 MB)
1 -Project Overview.mp4 (12.9 MB)
2 -SOLUTION Data Prep.mp4 (30.05 MB)
3 -SOLUTION K-Means Clustering.mp4 (112.82 MB)
4 -SOLUTION Hierarchical Clustering.mp4 (131.11 MB)
5 -SOLUTION DBSCAN.mp4 (42.34 MB)
6 -SOLUTION Compare, Recommend and Predict.mp4 (68.44 MB)
1 -Section Introduction.mp4 (4.01 MB)
10 -SOLUTION Isolation Forests.mp4 (90.93 MB)
11 -DBSCAN for Anomaly Detection.mp4 (5.88 MB)
12 -DBSCAN for Anomaly Detection in Python.mp4 (52.94 MB)
13 -Visualizing DBSCAN Anomalies.mp4 (34.56 MB)
14 -ASSIGNMENT DBSCAN for Anomaly Detection.mp4 (4.18 MB)
15 -SOLUTION DBSCAN for Anomaly Detection.mp4 (52.55 MB)
16 -Comparing Anomaly Detection Algorithms.mp4 (17.35 MB)
17 -RECAP Clustering and Anomaly Detection.mp4 (10.29 MB)
18 -Key Takeaways.mp4 (10.27 MB)
2 -Anomaly Detection Basics.mp4 (13.54 MB)
3 -Anomaly Detection Approaches.mp4 (32.45 MB)
4 -Anomaly Detection Workflow.mp4 (11.22 MB)
5 -Isolation Forests.mp4 (48.16 MB)
6 -Isolation Forests in Python.mp4 (40.46 MB)
7 -Visualizing Anomalies.mp4 (47.56 MB)
8 -Tuning and Interpreting Isolation Forests.mp4 (52.81 MB)
9 -ASSIGNMENT Isolation Forests.mp4 (7.43 MB)
1 -Section Introduction.mp4 (5.16 MB)
10 -SOLUTION Principal Component Analysis.mp4 (20.96 MB)
11 -Interpreting PCA.mp4 (29.93 MB)
12 -DEMO Interpreting PCA.mp4 (82.53 MB)
13 -ASSIGNMENT Interpreting PCA.mp4 (5.16 MB)
14 -SOLUTION Interpreting PCA.mp4 (56.51 MB)
15 -Feature Selection vs Feature Extraction.mp4 (21.98 MB)
16 -PCA Next Steps.mp4 (20.61 MB)
17 -T-SNE.mp4 (75.16 MB)
18 -T-SNE in Python.mp4 (56.16 MB)
19 -ASSIGNMENT T-SNE.mp4 (2.14 MB)
2 -Dimensionality Reduction Basics.mp4 (17.32 MB)
20 -SOLUTION T-SNE.mp4 (20.87 MB)
21 -PCA vs t-SNE.mp4 (13.54 MB)
22 -DEMO Dimensionality Reduction and Clustering.mp4 (61.43 MB)
23 -ASSIGNMENT T-SNE & K-Means Clustering.mp4 (2.39 MB)
24 -SOLUTION T-SNE & K-Means Clustering.mp4 (30.83 MB)
25 -Key Takeaways.mp4 (13.05 MB)
3 -Why Reduce Dimensions.mp4 (43.26 MB)
4 -Dimensionality Reduction Workflow.mp4 (15.46 MB)
5 -Principal Component Analysis.mp4 (64.25 MB)
6 -Principal Component Analysis in Python.mp4 (22.31 MB)
7 -Explained Variance Ratio.mp4 (18.86 MB)
8 -DEMO PCA and Explained Variance Ratio in Python.mp4 (35.75 MB)
9 -ASSIGNMENT Principal Component Analysis.mp4 (5 MB)
1 -Section Introduction.mp4 (6.34 MB)
10 -User-Item Matrix.mp4 (41.95 MB)
11 -ASSIGNMENT User-Item Matrix.mp4 (3.84 MB)
12 -SOLUTION User-Item Matrix.mp4 (36.03 MB)
13 -Singular Value Decomposition.mp4 (50.13 MB)
14 -Singular Value Decomposition in Python.mp4 (68.36 MB)
15 -ASSIGNMENT Singular Value Decomposition.mp4 (3.92 MB)
16 -SOLUTION Singular Value Decomposition.mp4 (27.84 MB)
17 -Choosing the Number of Components.mp4 (20.65 MB)
18 -DEMO Choosing the Number of Components.mp4 (69.5 MB)
19 -ASSIGNMENT Choosing the Number of Components.mp4 (4.79 MB)
2 -Recommenders Basics.mp4 (24.43 MB)
20 -SOLUTION Choosing the Number of Components.mp4 (63.22 MB)
21 -Making a Collaborative Filtering Recommendation.mp4 (43.59 MB)
22 -DEMO Making a Collaborative Filtering Recommendation.mp4 (56.84 MB)
23 -ASSIGNMENT Collaborative Filtering.mp4 (7 MB)
24 -SOLUTION Collaborative Filtering.mp4 (91.42 MB)
25 -Recommender Next Steps.mp4 (36.5 MB)
26 -DEMO Hybrid Approach.mp4 (25.2 MB)
27 -Key Takeaways.mp4 (15.55 MB)
3 -Content-Based Filtering.mp4 (9.67 MB)
4 -Cosine Similarity.mp4 (30.98 MB)
5 -Cosine Similarity in Python.mp4 (89.49 MB)
6 -Making a Content Based Filtering Recommendation.mp4 (48.64 MB)
7 -ASSIGNMENT Content-Based Filtering.mp4 (5.93 MB)
8 -SOLUTION Content-Based Filtering.mp4 (69.58 MB)
9 -Collaborative Filtering.mp4 (18.55 MB)]
Screenshot
[Image: f2froTAX_o.jpg]