A guide on how to automate posting Instagram Stories using Python and an unofficial API library, including code examples.
A curated list of recommended developer and IT Pro sessions for Microsoft Ignite 2020, tailored for Australian attendees.
Explains the theory behind linear regression models, a fundamental machine learning algorithm for predicting continuous numerical values.
A talk on implementing full-text search using only Django and PostgreSQL, presented at DjangoCon Europe 2020.
Compares Python for loops and list comprehensions, analyzing performance benchmarks and best use cases for filtering lists.
A tutorial on deploying a Django application to Azure App Service, Microsoft's serverless platform, to eliminate server management.
Compares Python's OrderedDict vs standard dict performance, explaining when and why OrderedDict is still useful.
A developer adds break display logic to a weekly schedule in a SaaS app, focusing on Django templates and styling.
A technical guide on migrating website comments from Commento to Utterances, a GitHub-based comment system, including steps and code.
A guide to testing machine learning code and systems, covering pre-train and post-train tests, evaluation, and implementation with a DecisionTree example.
Learn how to use Numba's @jit decorator to achieve massive speedups in Python code with minimal changes, demonstrated with a benchmark example.
A developer's final report on a Google Summer of Code project to integrate sparse and dense matrix support in QuTiP's core Qobj data type.
A technical article comparing while and for loops in Python for finding numbers, with performance benchmarks and Python version considerations.
A developer stream recap fixing task completion date bugs and adding student grade data to a Django SaaS app using test-driven development.
A review and tutorial on interpretable machine learning, covering Christoph Molnar's book and providing Python code examples for linear/logistic regression.
A review and tutorial covering Christoph Molnar's book on Interpretable Machine Learning, with Python code examples for linear and logistic regression.
The Dask team shares insights on running successful virtual community tutorials, including benefits for learners and maintainers, and practical logistics.
Author Yasoob releases the alpha version of his project-based Python book, offering a discount and free future updates.
Compares the 'Ask for Forgiveness' (EAFP) and 'Look Before You Leap' (LBYL) coding philosophies, using Python file reading as an example.
A series exploring techniques to write faster Python code, covering idiomatic patterns, performance tools, and benchmarking.
