What you’ll learn
- Understand and implement parallel computing concepts using Dask in Python
 - Work with large datasets using Dask DataFrames for scalable data manipulation
 - Perform advanced numerical computations using Dask Arrays and lazy evaluation
 - Build and optimize machine learning workflows with Dask-ML and joblib integration
 - Use Dask schedulers effectively for performance tuning and distributed computing
 - Profile performance, handle memory spilling, and apply best practices with Dask
 - Practice with real-world datasets like flight delays to build scalable ML models
 
How to Enroll Mastering Dask: Scale Python Workflows Like a Pro course?
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