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Matplotlib for Machine Learning

Visualize ML models like a pro and communicate AI insights with clarity!

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Matplotlib for Machine Learning
4 Modules

Course Curriculum

4 Modules · 13 Chapters · 14 Topics · 96 Sub-topics

01
Foundation
3 Chapters · 3 Topics · 18 Sub-topics
Introduction to Matplotlib
1 Topics
Introduction to Matplotlib
5 Sub-topics
What is Matplotlib and Why Use It
Installing Matplotlib and Verifying Setup
Understanding Pyplot vs Object-Oriented Interface
Your First Plot - Hello Matplotlib
Jupyter Notebook Integration and Magic Commands
Basic Plotting Fundamentals
1 Topics
Basic Plotting Fundamentals
6 Sub-topics
Understanding plot() Function Basics
Creating Simple Line Plots
Plotting Multiple Lines on One Graph
Setting X and Y Axis Data
Understanding Matplotlib's State Machine
Quick Styling with Format Strings
Figure and Axes Architecture
1 Topics
Figure and Axes Architecture
7 Sub-topics
Understanding Figure Objects
Understanding Axes Objects
Creating Figures with plt.figure()
Creating Figures with plt.subplots()
Figure Size and DPI Settings
Axes vs Axis - Clearing the Confusion
The Anatomy of a Matplotlib Plot
02
ML Visualization Basics
3 Chapters · 3 Topics · 23 Sub-topics
Scatter Plots
1 Topics
Scatter Plots
7 Sub-topics
Creating Basic Scatter Plots
Marker Size Variation by Data
Color Mapping by Data Values
Adding Color Bars
Marker Transparency and Overlapping Data
Scatter Plot with Different Marker Types
Bubble Charts
Line Plots and Customization
1 Topics
Line Plots and Customization
8 Sub-topics
Line Styles - Solid, Dashed, Dotted
Line Width and Transparency
Line Colors - Named, Hex, RGB
Markers - Types and Customization
Marker Size and Edge Properties
Creating Smooth Curves
Plotting Mathematical Functions
Step Plots and Fill Between
Heatmaps and 2D Representations
1 Topics
Heatmaps and 2D Representations
8 Sub-topics
Creating Heatmaps with imshow()
Creating Heatmaps with pcolor() and pcolormesh()
Adding Color Bars and Labels
Custom Color Maps
Interpolation Methods
Contour Plots
Filled Contour Plots
Contour Labels and Customization
03
Advanced ML Plots
3 Chapters · 3 Topics · 21 Sub-topics
Histograms and Distributions
1 Topics
Histograms and Distributions
7 Sub-topics
Creating Basic Histograms
Controlling Bin Number and Width
Histogram Customization and Styling
Multiple Histograms with Transparency
Cumulative Histograms
2D Histograms
Density Plots and KDE Overlays
Box Plots and Violin Plots
1 Topics
Box Plots and Violin Plots
7 Sub-topics
Creating Box Plots
Understanding Box Plot Components
Horizontal Box Plots
Multiple Box Plots for Comparison
Customizing Box Plot Appearance
Violin Plots Basics
Box Plots vs Violin Plots
Statistical Plots and Analysis
1 Topics
Statistical Plots and Analysis
7 Sub-topics
Regression Lines
Confidence Intervals
Moving Averages
Statistical Annotations
Probability Plots
Quantile Plots
Residual Plots
04
Model Evaluation
4 Chapters · 5 Topics · 34 Sub-topics
Subplots and Multiple Plots
1 Topics
Subplots and Multiple Plots
8 Sub-topics
Creating Subplots with plt.subplots()
Creating Subplots with plt.subplot()
Unequal Subplot Sizes with GridSpec
Nested Subplots
Sharing Axes Between Subplots
Tight Layout and Spacing
Subplot Labels and Titles
Creating Inset Plots
Working with Colors and Colormaps
1 Topics
Working with Colors and Colormaps
9 Sub-topics
Color Specification Methods
Named Colors and Color Codes
Built-in Colormaps Overview
Sequential Colormaps
Diverging Colormaps
Qualitative Colormaps
Creating Custom Colormaps
Color Normalization
Colorblind-Friendly Palettes
Integration with Other Libraries
1 Topics
Integration with Other Libraries
7 Sub-topics
Matplotlib with NumPy Arrays
Matplotlib with Pandas DataFrames
Plotting Directly from Pandas
Matplotlib with SciPy
Combining with Seaborn
Exporting to Plotly
Integration Best Practices
Real-World Applications and Best Practices
2 Topics
Real-World Applications and Best Practices - Part 1
5 Sub-topics
Scientific Publication Plots
Business Dashboard Components
Data Exploration Workflows
Report Automation
Common Mistakes to Avoid
Real-World Applications and Best Practices - Part 2
5 Sub-topics
Code Organization for Plotting
Documentation and Reproducibility
Testing Plot Functions
Accessibility and Universal Design
Future of Matplotlib and Alternatives

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