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Global Certification In Data Science & AI
GCDAI - Global Certification In Data Science & AI
01. GCDAI - Orientation Session (6th Jan 2024) (21:54)
02. Campaign Return on Marketing Investment - Practice Set
03. Introduction To Machine Learning (40:59)
04. Machine Learning - Data Science & AI Perspective (93:56)
05. Machine Learning - Linear Regression (171:30)
06. Machine Learning - Linear Regression Practice Sets (88:44)
07. Machine Learning - Practice Set Presentation by Team (110:34)
08. Machine Learning - Introduction To Logistics Regression (157:54)
09. Machine Learning - Logistics Regress Practice Set (Sales Prediction) (90:13)
10. Machine Learning - Project Presentation on Linear & Logistic Regression By Team (115:04)
11. Machine Learning - Decision Tree Classifier (116:55)
12. Machine Learning - Decision Tree - Practice Set Presentation (99:58)
13. Machine Learning - Random Forest Classifier (118:38)
14. Machine Learning - Random Forest Classifier - Practice Project (110:36)
15. Presentation By Team - Practice Sets (17:11)
16. Random Forest - Practice Set Discussion & Presentation (42:13)
17. Horse Survival Prediction - Random Forest ML - Class Discussion (17:31)
18. Naive Bayes Classifier & Practiceset presentation (97:44)
19. Naive Bayes Classifier - Presentation and Case Illustration (95:22)
20. Naive Bayes - Team Presentation (81:44)
21. KNN (K-Nearest Neighbor) ML Classifier (73:13)
22. KNN Classifier - Project Assignment Team Presentation (60:39)
23. K-Means Clustering - ML Algorithm (77:47)
24. K-Means Clustering - Walmart Case Study (58:36)
25. K-Means Clustering - Income Analyzer Team Presentation (46:46)
26. Hierarchical Clustering - ML Algorithm (42:22)
27. PCA - Dimensionality Reduction (86:03)
28. PCA - Case Study Discussion & Build PCA using SkLearn (74:59)
29. PCA - Project Assignment Presentation Discussion (33:31)
30. Team Presentation on Image Detection Case Studies using PCA (56:42)
31. Case Study Discussion - Uber Trip Prediction Case Study (10:04)
32. Case Study Presentation by Team - PCR and Uber Case Studies (74:54)
33. Introduction To Power BI - Reports Generation (145:34)
Machine Learning - Task Assignments & Practice Sets
01. Companies Profit Prediction - Linear Regression ML
02. Patient Diabetes Prediction - Logistic Regression ML
03. IRIS Leaf Species Detection - Decision Tree ML
04. Horse Survival Prediction - Random Forest ML
05. Shopping Prediction - Naive Bayes Classifier
06. Titanic Survival Prediction - Naive Bayes Classifier
07. Uber Use Case - Build a ML Model to Predict Trip Duration
08. Patient Diabetes Prediction - KNN Classifier
09. Income Spent Analysis : K-Means Clustering
10. Determine PCA : Covariance & Correlation Matrix, Eigen Vectors and Values
11. Image Prediction Using PCA
Value Propositions
Mastering Machine Learning with Python (Ebook - Download)
Interview Questions - Python, ML (E-Book - Download)
Machine Learning Algorithm (EBook - Download)
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06. Titanic Survival Prediction - Naive Bayes Classifier
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