Master Scalable Data Processing, Parallel Computing, and Machine Learning Workflows Using Dask in Python
What you will learn
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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
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