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More Python Tips, Tricks, and Techniques for Data Science

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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

Introduction
  • Tips and tricks in Python
1. IPython and Jupyter Notebook
  • Accessing methods and documentation
  • Errors and debugging
  • Code profiling and timing
2. NumPy and Pandas
  • Essentials of NumPy arrays
  • Broadcasting
  • Comparison, masks, and Boolean logic
  • Pandas indexing and subsetting
  • Handling missing data
  • Aggregation and grouping
  • Querying and filtering data
3. Visualization with Matplotlib
  • General plotting tips
  • Adding text and annotations
  • Multiple subplots
4. Machine Learning Tips
  • sklearn Estimator API
  • Model validation and hyperparameter tuning
  • Feature engineering
  • Creating machine learning pipelines
Conclusion
  • Next steps

Taught by

Harshit Tyagi

Reviews

4.6 rating at LinkedIn Learning based on 106 ratings

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