Packt - Python Data Science Essentials

1. 2.Data Munging/07.Data Loading and Preprocessing.mp470.02MB
2. 1.First Step/02.Introducing Data Science and Python.mp45.78MB
3. 1.First Step/03.Getting Ready.mp413.13MB
4. 1.First Step/04.A Glance at the Essential Packages.mp46.12MB
5. 1.First Step/05.Introducing the Jupyter Notebook.mp444.37MB
6. 1.First Step/06.Scikit-learn Toy Datasets.mp450.22MB
7. 1.First Step/01.The Course Overview.mp412.23MB
8. 2.Data Munging/08.Working with Categorical and Text Data.mp442.91MB
9. 2.Data Munging/09.Creating NumPy Arrays.mp443.11MB
10. 2.Data Munging/10.NumPy's Fast Operations and Computations.mp418.86MB
11. 3.The Data Pipeline/11.Introducing EDA.mp414.33MB
12. 3.The Data Pipeline/12.Building New Features.mp416.41MB
13. 3.The Data Pipeline/13.Dimensionality Reduction.mp427.95MB
14. 3.The Data Pipeline/14.The Detection and Treatment of Outliers.mp424.39MB
15. 3.The Data Pipeline/15.Validation Metrics.mp424.83MB
16. 3.The Data Pipeline/16.Testing and Validating.mp425.96MB
17. 3.The Data Pipeline/17.Cross-Validation.mp425.8MB
18. 3.The Data Pipeline/18.Hyperparameter Optimization.mp425.89MB
19. 3.The Data Pipeline/19.Feature Selection.mp421.6MB
20. 3.The Data Pipeline/20.Wrapping Everything in a Pipeline.mp424.79MB
21. 4.Machine Learning/21.Preparing Tools and Datasets.mp410.93MB
22. 4.Machine Learning/22.Linear and Logistic Regression.mp415.89MB
23. 4.Machine Learning/23.Naive Bayes.mp412.01MB
24. 4.Machine Learning/24.K-Nearest Neighbors.mp47.23MB
25. 4.Machine Learning/25.An Overview of Unsupervised Learning.mp435.51MB