Based on our record, NumPy should be more popular than Augur. It has been mentiond 107 times since March 2021. 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.
People have brought new markets such as virtual lands and more to the limelight. Some of them include Kirin's learn-to-earn project, in which you can answer quizzes and tests to earn crypto assets, Aavegotchi and YOLOrekt's bid to earn. They are distinct, but they both perform the same B2E function. In Aavegotchi, the Aavegotchi B2E auction modifies at least one of the four personality traits of an Aavegotchi:... Source: over 1 year ago
Yes “handicappers” come up with the odds/spread for sports and some off the wall stuff. “Prediction markets” is a big thing in crypto. And yes you can create your own “outcome” for an event that people can bet on. If you wanna check out the most popular prediction market and see all the crazy things people are betting on here’s Augur https://augur.net/. Source: almost 2 years ago
It's not exactly new? There were several general betting market in crypto, but they never got much popularity. https://augur.net/ https://polymarket.com/. - Source: Hacker News / almost 2 years ago
Example of web 3 platforms are Steemit, Diaspora, Augur, Opensea, Everledger among many others while examples of Web 2 platforms are Facebook, Twitter, Binance, Upwork. - Source: dev.to / about 2 years ago
Https://augur.net (bets on real world events). Source: over 2 years 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
TellApart - TellApart helps companies turn individual customer preferences into sales by predicting which items customers are most interested in
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
TradeX - TradeX is an exchange to bet on the predicted outcome of an upcoming event, like the number of covid cases, inflation rate, or the next president.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Predicto - Make predictions on the Blockchain
OpenCV - OpenCV is the world's biggest computer vision library