Grin Gaming Reviews

NumPy Reviews

Grin Gaming mentions (7)

• For anyone still wondering what SmileCoin is all about check out their roadmap and think about stocking up before they release the dApp this month!

  Anyways, just wondering what the details are here, we can help send those to your wallet manually. Can you please reach out to my name at gringaming.com and we'll take it from there? Source: over 2 years ago

• SMILE yieldly

  You can also earn it at gringaming.com . They are "supposed" to be implementing the withdraws of the coin to an algo wallet this week. If they finally follow through with that it will be great. Source: over 2 years ago

• A result of Tinyman action and Yieldly pool I would imagine? I'm not aware of any other notable news from them recently.

  No, SMILE is the native coin for gringaming.com. Source: over 2 years ago

• Smile

  Grin Gaming lets you earn SMILE, but no way to place bets with or withdraw the SMILE earned yet. Bets have to be placed with USD, winnings can be claimed in either USD or SMILE+20% Bonus. IDK if there are any other active use cases. Source: over 2 years ago

• ASA roundup.

  Play predictive games and farm SMILE on Grin Gaming (withdrawal to Algorand wallet coming soon). Source: over 2 years ago

NumPy mentions (107)

• 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

• Beginning Python: Project Management With PDM

  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 / 8 months ago