Overview
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Deliver valuable insights to your users with Python. Get practical tips and techniques that can help you enhance your Python data science workflow.
Syllabus
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Introduction
- Tips and tricks in Python
- Accessing methods and documentation
- Errors and debugging
- Code profiling and timing
- Essentials of NumPy arrays
- Broadcasting
- Comparison, masks, and Boolean logic
- Pandas indexing and subsetting
- Handling missing data
- Aggregation and grouping
- Querying and filtering data
- General plotting tips
- Adding text and annotations
- Multiple subplots
- sklearn Estimator API
- Model validation and hyperparameter tuning
- Feature engineering
- Creating machine learning pipelines
- Next steps
