Based on our record, Scikit-learn seems to be a lot more popular than Officevibe. While we know about 28 links to Scikit-learn, we've tracked only 2 mentions of Officevibe. 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.
Hey HN! I am asking out of genuine curiosity, and perhaps doing a little market research. My team uses https://www.donut.com/ and https://officevibe.com/ but I'm pretty sure we're on the free tier for both. Do you work in a team that pays monthly for any cool Slack apps or integrations? Which ones? If you're not the one paying, do you find it useful - or annoying? Cheers! - Source: Hacker News / over 1 year ago
Officevibe, which is an employee experience platform, regularly sends out Slack notifications on behalf of their customers asking employees to complete a brief survey. Their engineering team utilizes the Automations API to create lists of users for whom the Slack survey could not be delivered and send them an email survey instead. - Source: dev.to / about 2 years ago
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
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 / 12 months ago
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
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
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: over 1 year ago
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