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4 Chapters · 48 Lessons

Advanced Data Analysis

Data Visualization and Machine Learning with Python

My Courses

Chapter 1

Visual Storytelling using Matplotlib

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Lessons

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Introduction to Matplotlib for Data Visualization

Plotting with plt.plot()

Customizing Lines and Markers

Adding Titles, Labels, and Legends

Creating Bar and Pie Charts

Anatomy of a Matplotlib Plot

Multiple-choice quiz

Multiple Subplots and Figures

Saving Plots to File

Styling and Themes

Fill-in-the-blank quiz

Chapter 2

Elegant Statistical Graphics with Seaborn

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Lessons

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Introduction to Seaborn

Seaborn vs. Matplotlib

Categorical Plots (barplot, countplot)

Distribution Plots (histplot, kdeplot)

Relational Plots in Seaborn – Scatter and Line Plots

Visualizing Relationships with Seaborn

Multiple-choice quiz

Grouping and Hue for Comparisons in Seaborn

Pair Plots and Heatmaps in Seaborn

Plot Customization and Themes in Seaborn

Multi-Plot Grids (FacetGrid, lmplot)

Fill-in-the-blank quiz

Chapter 3

Scientific Computing with SciPy

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Chapter 4

Machine Learning with Scikit-learn

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Lessons

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Introduction to Scikit-learn

The Machine Learning Workflow

Types of ML - Supervised vs Unsupervised

Dataset Structure - Features and Labels

Splitting Data - Train vs Test

ML Workflow and Model Lifecycle

Feature Scaling and Preprocessing

Multiple-choice quiz

Classification with K-Nearest Neighbors

Regression with Linear Models

Evaluating Classification Models

Evaluating Regression Models

Introduction to Clustering (K-Means)

What is Cross-Validation?

Fill-in-the-blank quiz