Practical Deep Learning for Data Scientists
Hands-on PyTorch and GPU Deep Learning tutorial for data scientists. Build common architectures, evaluate performance, and leverage compute resources effectively. Ideal for those with ML basics seeking practical DL experience.
Introduction to Property-Based Testing
Discover property-based testing with Hypothesis, learn to write robust tests, and find real bugs. Hands-on experience in creating generalized tests for diverse scenarios.
Time for Time Series
Explore time series analysis fundamentals, decomposition techniques, and forecasting models using Pandas. Learn to extract insights and create powerful predictions from temporal data.
From Spreadsheets to DataFrames
Learn to transition from spreadsheets to Python DataFrames, exploring web scraping, data processing, analysis, and visualization using popular libraries like Pandas and Matplotlib. Gain skills for efficient data management and problem-solving.
Writing Documentation with Sphinx and reStructuredText
Learn to create Python documentation using reStructuredText and Sphinx. Master essential skills for contributing to open source projects by improving their documentation and overcoming barriers to entry.
A Complete Beginner's Guide to Python by Making Simple Games
Learn Python basics through creating simple games. Covers variables, expressions, loops, and functions. Ideal for complete beginners, with guidance for further learning.
Hands-On Regular Expressions in Python
Learn to create, understand, and effectively use regular expressions in Python for data validation, parsing, and normalization. Discover when and how to apply regex for optimal results.
Dashboards for All
Learn to create interactive dashboards using Python libraries like Bokeh and Panel. Explore data visualization techniques, analyze diverse datasets, and tell compelling stories through customized, user-friendly interfaces.
Hacking Dask - Diving Into Dask's Internals
Explore advanced Dask features: task graph optimization, plugins, cluster inspection. Gain deeper understanding of internals and apply to data-intensive workloads.
Python Unit Testing with Pytest and Mock
Learn to write high-quality Python unit tests using Pytest and mock. Master best practices for effective testing, enhancing code reliability and maintainability.
Python Packaging Demystified
Hands-on tutorial demystifying Python packaging, covering libraries and applications, build tools, distribution formats, and testing techniques for both beginners and experienced developers.
Functional Python
Explore functional programming concepts in Python, including higher-order functions, immutability, and lazy evaluation. Learn to write cleaner, more efficient code using functional paradigms.
Python Performance at Scale - Making Python Faster at Instagram
Explore Instagram's Python optimization strategies, including runtime modifications, inline caching, and JIT compilation, achieving significant performance improvements for large-scale web applications.
Using Declarative Configs for Maintainable Reproducible Code
Explore declarative configs for maintainable, reproducible code. Learn input formats, representations, deserialization, and type-safety. Discover strategies for evolving configs while preserving backwards compatibility.
What Are Quantum Computers, and How Can We Train Them in Python
Explore quantum computing in Python: access real quantum hardware, differentiate quantum programs, and integrate them into larger differentiable programs for optimization and training.
Protocol - The Keystone of Type Hints
Explore static duck typing in Python using typing.Protocol, enhancing type hints for more expressive and verifiable code. Learn concepts and benefits through real-world examples from the standard library.
An Introduction to FastAPI
Explore FastAPI's features for rapid REST API development in Python, covering core concepts, schema creation, documentation, and advanced functionalities.
Static Sites with Sphinx and Markdown
Explore Sphinx for building static websites using Markdown, leveraging its powerful features for rich linking and knowledge base creation beyond traditional documentation.
When Is an Exception Not an Exception? Using Warnings in Python
Explore Python's warning system for handling minor issues without raising exceptions. Learn to generate, filter, and customize warnings for more nuanced error handling in your code.
CI-CD 101
Hands-on introduction to CI/CD fundamentals using CircleCI. Learn core principles, build configuration, code commits, testing, and packaging through practical exercises.
Intro to Pydantic - Run-Time Type Checking for Your Dataclasses
Explore Pydantic for runtime type checking in Python, enhancing data validation for web APIs using standard type annotations and offering compatibility with dataclasses.