Leanbe.ai Reviews

Scikit-learn Reviews

Leanbe.ai mentions (7)

• Not once posted about our tool and got your advice. We are implementing them

  A lot of times here in this subreddit we talked about Beupify and finally me, with the team worked on your feedback and we would have absolutely different and new website just in 2 weeks. I am here to ask you again for feedback as there is left not that much time so we can implement other suggestions as well. For the ones who are not familiar with the tool, I would love to mention that it was only a tool to... Source: about 3 years ago

• First meeting with the investors. What should I have to have in my mind?

  If it's not against the tools of the subreddit - you can check the website and give me some advice if possible. Source: about 3 years ago

• My simple tactic! How we got 2.5K users in 7 months for our SaaS

  Guys, you were writing me about the startup - here is it https://beupify.com/. Source: about 3 years ago

• 7 months - 2.5K B2B customers!

  You can check out the tool, and ping me if you have any questions! Source: about 3 years ago

• Thank you all for your dedicated feedback and support. We got our first 2000 customer

  Here are some tips that helped us to scale our business. P.S The tool is Beupify which is an all-in-one solution for the release notes :). Source: over 3 years ago

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 / 17 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