Python Programming

11.
Application Areas
11.2.
Data Science
11.2.1.
Data Manipulation
11.2.1.1.
NumPy
11.2.1.1.1.
Arrays
11.2.1.1.1.1.
Array Creation
11.2.1.1.1.2.
Array Operations
11.2.1.1.3.
Broadcasting
11.2.1.2.
Pandas
11.2.1.2.1.
DataFrames
11.2.1.2.1.1.
DataFrame Creation
11.2.1.2.1.2.
Data Selection
11.2.1.2.1.3.
Data Cleaning
11.2.1.2.2.
Series Objects
11.2.1.2.3.
Data Import/Export
11.2.1.2.3.1.
CSV Files
11.2.1.2.3.2.
Excel Files
11.2.2.
Data Visualization
11.2.2.1.
Matplotlib
11.2.2.1.1.
Basic Plotting
11.2.2.1.1.1.
Line Plots
11.2.2.1.1.2.
Scatter Plots
11.2.2.1.1.3.
Bar Charts
11.2.2.1.2.
Plot Customization
11.2.2.1.2.1.
Labels and Titles
11.2.2.1.2.2.
Colors and Styles
11.2.2.2.
Seaborn
11.2.2.2.1.
Statistical Plots
11.2.2.2.1.1.
Distribution Plots
11.2.2.2.1.2.
Relationship Plots
11.2.2.2.2.
Plot Aesthetics
11.2.3.
Machine Learning
11.2.3.1.
Scikit-learn
11.2.3.1.1.
Model Training
11.2.3.1.1.1.
Supervised Learning
11.2.3.1.2.
Model Evaluation
11.2.3.1.2.1.
Cross-Validation
11.2.3.1.2.2.
Metrics
11.2.3.2.
Deep Learning Frameworks
11.2.3.2.1.
TensorFlow
11.2.3.2.1.1.
Neural Networks
11.2.3.2.1.2.
Model Building
11.2.3.2.2.
PyTorch
11.2.3.2.2.1.
Tensors
11.2.3.2.2.2.
Autograd System
11.4.
Testing
11.4.1.
Unit Testing
11.4.1.1.
unittest Module
11.4.1.1.1.
Test Cases
11.4.1.1.2.
Test Methods
11.4.1.1.3.
Assertions
11.4.1.1.4.
Test Discovery
11.4.2.
pytest Framework
11.4.2.2.
Fixtures
11.4.2.2.2.
Fixture Scopes
11.4.2.4.
Test Organization
11.4.2.4.1.
Test Files
11.4.2.4.2.
Test Classes

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10. Advanced Python Concepts

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1. Introduction to Python