1.1 Data Science with Jupyter.zip
1. The Course Overview
2. Jupyter User Interface
3. Jupyters Menu Choice
4. Real Life Examples Finance and Gambling
5. Real Life Examples Insurance and Consumer Products
6. Installing JupyterHub
7. Optimizing Python Script
8. Optimizing R Scripts
9. Securing a Notebook
10. Heavy-Duty Data Processing Functions in Jupyter
11. Using Pandas in Jupyter
12. Using SciPy in Jupyter
13. Expanding on Panda DataFrames
14. Sorting and Filtering DataFrames
15. Making a Prediction Using scikit-learn
16. Making a Prediction Using R
17. Interactive Visualization and Plotting
18. Drawing a Histogram of Social Data
19. Using Spark to Analyze Data
20. Using SparkSession and SQL
21. Combining Datasets
22. Loading JSON into Spark
23. Analyzing 2016 US Election Demographics
24. Analyzing 2016 Voter Registration and Voting
25. Analyzing Changes in College Admissions
26. Predicting Airplane Arrival Time
27. Reading a CSV File
28. Manipulating Data with dplyr
29. Tidying Up Data with tidyr
30. Visualizing Glyph Ready Data
31. Publishing a Notebook
32. Creating a Shiny Dashboard
33. Building Standalone Dashboards
34. Converting JSON to CSV
35. Evaluating Yelp Reviews
36. Naive Bayes
37. Nearest Neighbor Estimator
38. Decision Trees
39. Neural Networks and Random Forests
40. Test your knowledge.html