Based on our record, Matomo should be more popular than Scikit-learn. It has been mentiond 82 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.
Matomo just released their major v5 upgrade with following key improvements:. - Source: dev.to / 5 months ago
There are many good, lightweight, and open-source alternatives to Google Analytics, such as Plausible, Matomo, Fathom, Simple Analytics, and so on. Many of these options are open-source, and can be self-hosted. - Source: dev.to / 7 months ago
You can for example use analytics that aren't spyware, and hence don't even have to try to trick users giving "consent" to things they don't really want. Seriously: what share of people actually want their behavior to be tracked for ad companies to make more money? https://matomo.org/. - Source: Hacker News / 9 months ago
Matomo is a GDPR-compliant and open-source analytics platform. You can either host it yourself or use Matomo’s hosted version. https://matomo.org/. - Source: Hacker News / 9 months ago
I tried the self-hosted version of Matomo [1][2] a few years back but I remember it was a bit underwhelming for the effort required to set it up. https://matomo.org. - Source: Hacker News / 12 months 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 / about 1 year 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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Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Plausible.io - Plausible Analytics is a simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics. Made and hosted in the EU, powered by European-owned cloud infrastructure 🇪🇺
OpenCV - OpenCV is the world's biggest computer vision library
Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.
NumPy - NumPy is the fundamental package for scientific computing with Python