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Learn X in Y minutes might be a bit more popular than NumPy. We know about 146 links to it since March 2021 and only 107 links to NumPy. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
> Sure, maybe for some esoteric edge cases, but 5 mins on https://learnxinyminutes.com/ should get you 80% of the way there, and an afternoon looking at big projects or guidelines/examples should you another 18% of the way. Not for C++, and even for other languages, it's not the language that's hard, it's the idioms. Python written by experts can be well-nigh incomprehensible (you can save typing out... - Source: Hacker News / about 1 month ago
> Learning a new language shouldn't be difficult. Programmers are expected to familiarize themselves with new tech. I wish any large company agreed with this. I've worked for a company that on boarded every single new engineer to a very niche language (F#) in a few days. Also, everybody I worked with there was amazing. Probably because of that kind of mindset. Meanwhile google tiptoes around teams adopting kotlin... - Source: Hacker News / about 1 month ago
When I want to get a quick feel for a language I've never heard of, I usually look for the Learn X in Y Minutes[0] page for it. Shen doesn't have one. Perhaps the author and/or poster should remedy that? [0] https://learnxinyminutes.com/. - Source: Hacker News / about 2 months ago
Learn x in y minutes: Concise tutorials to learn various programming languages and tools quickly. - Source: dev.to / 2 months ago
StackOverflow's making their own competing LLM for all this stuff. IMO, one of the biggest problems with the way people use LLMs right now, is that they're being treated as a single oracle: to know Java, it must be trained on examples of Java. It would be much better if their language comprehension abilities were kept separated from their knowledge (and there are development efforts in this direction), so in this... - Source: Hacker News / 3 months ago
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
Exercism.io - Download and solve practice problems in over 30 different languages.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
SyntaxDB - Easily look up programming syntax for multiple languages
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Month to Master - Learn anything in 30 days, with the help of an AI coach
OpenCV - OpenCV is the world's biggest computer vision library