Litecoin VS Scikit-learn

Litecoin Reviews

Scikit-learn Reviews

Litecoin mentions (34)

• The number of LTC addresses is skyrocketing!

  The price of Litecoin just barely went over its 2017 peak, which to many sounds bad, although 80-90% of all cryptocurrencies failed during the 2018 bear run, so litecoin has still beat the majority of the market. Source: 11 months ago

• Do LTC MWEB transaction fees go up proportionally to regular transaction fees?

  But, it's quite easy to go, download Litecoin Core and play with it. (https://litecoin.org/). Source: about 1 year ago

• A Deep Dive Into Tokenization

  A crypto coin is simply a digital coin, created for making payments. Coins are created to act like money: in other words, they represent a unit of account, store of value, and medium of transfer. Crypto coins tend to take the form of their native blockchain, like with Bitcoin (BTC), Bitcoin Cash (BCH), Litecoin (LTC) and Monero (XMR). Source: about 1 year ago

• LiteCoin till October!

  Yes. And harder to mine. The reward for miners becomes 6 coins instead of the twelve you receive when proofing (finding) a block. The value does happen right away.. It takes years of people collecting and holding. The amount of coins will remain the same. Not like the US government who can print money at will. 😂 Litecoin.org. Source: over 1 year ago

• Litecoin Records Certain Milestones In 2022 Despite The General Downtrend

  According to a Litecoin tweeter post, The Litecoin Network completed over 39 million transactions in 2022. Source: over 1 year 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