Scikit-learn Reviews

Glambase Reviews

1. wasamasif22

   3 months ago
   Dynamic Platform

   I recently had the opportunity to explore this platform, and I must say, I'm impressed by its user-friendly interface and real-time analytics. The seamless integration with social media not only facilitates engagement but also enhances the overall experience. Additionally, the autonomy and interactive behaviour capabilities add a layer of personalisation that sets it apart. While there are minor drawbacks, such as limited physical traits customisation, the platform's early adopter benefits and rewarding early access system more than make up for it. Overall, it's a for anyone looking to leverage technology for profit generation without needing extensive technical knowledge.

2. Tony Miller

   3 months ago

   The most technologically advanced website I've ever worked on. Real-time analytics, there is integration with social networks, but everything is clear and you do not need deep technical knowledge.

3. Arthur Kaiser

   3 months ago
   Glambase impresses with its user-friendly platform

   Glambase impresses with its user-friendly platform that requires no technical knowledge, making it accessible to all. The real-time analytics feature stands out, providing valuable insights for informed decision-making. The interactive behavior capability enhances user engagement, creating a dynamic experience. Additionally, the physical traits customization and personality traits customization options add a personal touch, making interactions more engaging. While minor improvements could enhance the platform further, Glambase's functionality and ease of use make it a valuable tool for users seeking customization and real-time insights.

Scikit-learn mentions (29)

• Essential Deep Learning Checklist: Best Practices Unveiled

  How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 15 days ago

• 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 / 4 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 / about 1 year 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

Glambase mentions (0)