Have you heard about Python decorators? Not only do these special functions have a funny name, but their syntax differs from standard Python code (they attach to other functions through use of the @ sign).
No wonder many beginners avoid decorators at all costs! However, we’ve got good news for you. Decorating your functions isn’t as hard as it looks — and it results in cleaner, more modular programs with less boilerplate code.
As this programming language becomes more prevalent, to fulfill our mission to upskill the world’s workforce in the careers of the future — we’re launching the all-new Intermediate Python Nanodegree program that is open for enrollment today.
Working from home, a privilege traditionally only enjoyed by employees of progressive tech companies, has now become the norm.
COVID-19 has changed the world in many ways this past year, and the shift in companies offering remote-friendly jobs has been unprecedented. According to a recent Stanford research survey, 42% of workers are now working from home on a full-time basis.
If you’ve always dreamed of spending your workday coding and building iPhone apps, but didn’t want to pack up and move to the pricey Bay Area, you’re in luck. Many companies, from early startups to tech giants like Twitter, have made the decision to close their offices in favor of a fully remote workforce.
Whether you work on large-scale data analysis, are interested in geospatial modeling or want to solve linear equations in your deep learning applications, you’ll sooner or later come across the NumPy library for numerical computing.
This powerful framework lets you process your tabular data at a high speed. But what is a NumPy array, and how can you make the most of it?