Ethereum Reviews

Scikit-learn Reviews

Ethereum mentions (148)

• How I Contributed One Line of Code to Ethereum

  After my first open-source contribution, I looked for other projects where I could contribute. One of those projects was Ethereum, which is a blockchain network that enables Decentralized Finance, tokenization of assets, and an open internet. While reading through their contributing guidelines, I found an issue in their documentation and ended up fixing it, making my second open-source contribution. - Source: dev.to / 6 months ago

• What’s The Difference Between Bitcoin And Bitcoin Cash?

  Keep up to date with Bitcoin on Bitcoin.org Keep up to date with Ethereum news on Ethereum.org. Source: 7 months ago

• Roadmap to Becoming a Web3 Developer in 2023

  Ethereum - The second biggest cryptocurrency platform after Bitcoin, with its own blockchain and smart contract functionality through Solidity. - Source: dev.to / 9 months ago

• Coinbase revolutionizes Ethereum communication

  Coinbase makes use of the Extended Message Transfer Protocol (XMTP) communication protocol to allow messaging between Ethereum addresses. Source: 10 months ago

• Direct-to-Creator generation

  Elsewhere, The Sandbox is a blockchain-based virtual world built on Ethereum where players can build, own and monetise their gaming experiences. The platform utilises a ‘play-to-earn’ model to incentivise players for time spent in the metaverse, and is building an open metaverse to enable greater collaboration with creators and brands alike. Source: 11 months ago

Scikit-learn mentions (28)

• How to Build a Logistic Regression Model: A Spam-filter Tutorial

  Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 3 months ago

• Link Prediction With node2vec in Physics Collaboration Network

  Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago

• WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point

  The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago

• PSA: You don't need fancy stuff to do good work.

  Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago

• Help on using R for Machine Learning?

  Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago