NumPy Reviews

Clojure Reviews

NumPy mentions (108)

• 2 Minutes to JupyterLab Notebook on Docker Desktop

  Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 9 months ago

• Element-wise vs Matrix vs Dot multiplication

  In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 3 months ago

• JSON in data science projects: tips & tricks

  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 / 3 months ago

• Introducing Flama for Robust Machine Learning APIs

  Numpy: A library for scientific computing in Python. - Source: dev.to / 6 months ago

• A Comprehensive Guide to NumPy Arrays

  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 / 7 months ago

Clojure mentions (37)

• Moving your bugs forward in time

  ‍For the rest of this post I’ll list off some more tactical examples of things that you can do towards this goal. Savvy readers will note that these are not novel ideas of my own, and in fact a lot of the things on this list are popular core features in modern languages such as Kotlin, Rust, and Clojure. Kotlin, in particular, has done an amazing job of emphasizing these best practices while still being an... - Source: dev.to / 28 days ago

• Let's write a simple microservice in Clojure

  This article will explain how to write a simple service in Clojure. The sweet spot of making applications in Clojure is that you can expressively use an entire rich Java ecosystem. Less code, less boilerplate: it is possible to achieve more with less. In this example, I use most of the libraries from the Java world; everything else is a thin Clojure wrapper around Java libraries. - Source: dev.to / about 1 month ago

• A new F# compiler feature: graph-based type-checking

  I have a tangential question that is related to this cool new feature. Warning: the question I ask comes from a part of my brain that is currently melted due to heavy thinking. Context: I write a fair amount of Clojure, and in Lisps the code itself is a tree. Just like this F# parallel graph type-checker. In Lisps, one would use Macros to perform compile-time computation to accomplish something like this, I think.... - Source: Hacker News / 7 months ago

• Ask HN: Why does the Clojure ecosystem feel like such a wasteland?

  As an analogy - my face hasn't changed all that much in a past few years, and I haven't changed my profile picture in those few years. Does it really mean that I'm unmaintained/dead? > Where can I find latest documentation [...]? The answer is still https://clojure.org/. And https://clojuredocs.org/ but it's community-maintained so might occasionally be missing some things right after they're released. E.g. As of... - Source: Hacker News / 9 months ago

• Best implementation of CL for learning purposes

  As a Java/Scala user you should check out Clojure! It is highly recommended (https://clojure.org). Source: about 1 year ago