1. About this Section
2. Quick Tips Uploading Files in Snowflake
3. Introduction Snowpark Components
4. Introduction Procedures and Functions from SQL
5. Introduction Snowpark for Python
6. Introduction Procedures and Functions from Python
7. Introduction Vectorized User-Defined Functions
8. Introduction Runtimes and Package Versions
9. Introduction Snowpark for ML Pipelines
10. Data Collection Populating with SQL Statements
11. Data Collection Synthetic Data Generation
12. Data Collection Faker Library in Python Worksheet
13. Quick Tips Easiest Way to Connect to Snowflake
14. Data Collection Uploading with SQL Scripts
15. Data Collection Uploading with Python Code
16. Data Collection Uploading from External Stages
17. Data Collection Uploading Other Datasets
18. Data Collection Sample Data Extraction
19. Data Collection Data Split
20. Quick Checkpoint About Ingesting Data in Snowflake
21. Quick Tips Correlation Heatmap in Snowflake
22. Data Exploration Snowsight Charts and Dashboards
23.1 Exploratory Data Analysis with Snowflake and Deepnote.html
23.2 Seamless Machine Learning Workflows with Snowpark & Deepnote.html
23. Data Exploration Snowflake Partner Notebooks
24.1 Build and Deploy ML with Ease Using Snowpark ML, Snowflake Notebooks, and Snowflake Feature Store.html
24.2 Diamond Price Prediction End-to-End Machine Learning with Snowpark ML in Snowflake Notebooks.html
24. Data Exploration Snowflake Notebooks
25. Data Exploration Overview
26. Quick Tips Data Profiling in Snowflake
27. Quick Checkpoint Pandas vs Snowpark Data Frames
28.1 Snowpark Python Top Three Tips for Optimal Performance.html
28. Feature Engineering Pandas vs Snowpark DataFrames
29.1 End to end Machine Learning with Scikit-Learn and Snowpark.html
29. Feature Engineering Using Pandas DataFrames
30.1 How to Create a Complex Query with Snowpark DataFrame in Python.html
30. Feature Engineering Using Snowpark DataFrames
31. Feature Engineering Scalability Check with Python Worksheets
32.1 Snowpark API The Object Model.html
32. Feature Engineering Overview
33.1 How to Generate Snowflake Stored Procs via Python Worksheets.html
33. Quick Checkpoint About the Python Worksheets
34. Quick Tips DataFrame Queries
35. Data Preprocessing When You Cannot Avoid Pandas
36. Model Training Sentiment Analysis in Local Mode
37.1 NLP and ML with Snowpark Python and Streamlit for Sentiment Analysis.html
37. Model Training Sentiment Analysis with Stored Procedure
38. Model Training Overview
39. Model Training Sentiment Analysis with Imported Modules
40.1 Getting Started with Snowpark for Python with Scikit-learn.html
40. Model Training House Predictions with Stored Procedure
41. Model Serving Overview
42. Model Serving Sentiment Predictions with UDFs
43. Model Serving Sentiment Predictions with SQL
44.1 Vectorized UDFs for Batching.html
44. Model Serving House Predictions with Vectorized UDF
45.1 Examining the performance benefits of the Cachetools library.html
45. Model Serving Introduction to Cachetools
46. Model Serving UDFs vs Vectorized UDFs
47. Test Your Knowledge.html