Interactive Python Learning with marimo

Explore our collection of interactive notebooks for Python, data science, and machine learning.

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Why Learn with Marimo?

Interactive Learning

Learn by doing with interactive notebooks that run directly in your browser.

Practical Examples

Real-world examples and applications to reinforce your understanding.

Comprehensive Curriculum

From Python basics to advanced machine learning concepts.

Explore Our Courses

Daft

title: Readme marimo-version: 0.18.4

1 notebooks:
  1. What Makes Daft Special

Duckdb

title: Readme marimo-version: 0.18.4

5 notebooks:
  1. Getting Started
  2. Loading Parquet
  3. Loading Json
  4. Working With Apache Arrow
  5. Duckdb Loading Csvs

Functional Programming

title: Readme marimo-version: 0.18.4

2 notebooks:
  1. Functors
  2. Applicatives

Optimization

title: Readme marimo-version: 0.18.4

7 notebooks:
  1. Least Squares
  2. Linear Program
  3. Minimum Fuel Optimal Control
  4. Quadratic Program
  5. Portfolio Optimization
  6. Convex Optimization
  7. Sdp

Polars

title: Readme marimo-version: 0.18.4

15 notebooks:
  1. Why Polars
  2. Dataframes
  3. Loading Data
  4. Basic Operations
  5. Reactive Plots
  6. Dataframe Transformer
  7. Querying-With-Sql
  8. Working With Columns
  9. Data Types
  10. Strings
  11. Missing Data
  12. Aggregations
  13. Window Functions
  14. User Defined Functions
  15. Lazy Execution

Probability

title: Readme marimo-version: 0.18.4

21 notebooks:
  1. Sets
  2. Axioms
  3. Probability Of Or
  4. Conditional Probability
  5. Independence
  6. Probability Of And
  7. Law Of Total Probability
  8. Bayes Theorem
  9. Random Variables
  10. Probability Mass Function
  11. Expectation
  12. Variance
  13. Bernoulli Distribution
  14. Binomial Distribution
  15. Poisson Distribution
  16. Continuous Distribution
  17. Normal Distribution
  18. Central Limit Theorem
  19. Maximum Likelihood Estimation
  20. Naive Bayes
  21. Logistic Regression

Python

title: Readme marimo-version: 0.18.4

10 notebooks:
  1. Numbers
  2. Strings
  3. Collections
  4. Conditional Logic
  5. Loops
  6. Dictionaries
  7. Advanced Collections
  8. Functions
  9. Modules
  10. Exceptions

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Help us improve these learning materials by contributing to the GitHub repository. We welcome new content, bug fixes, and improvements!

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