Scikit-learn Reviews

Clipdrop Reviews

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 / 12 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: over 1 year ago

Clipdrop mentions (19)

• Difference between burguer and hamburguer?

  I'm trying to use stable diffusion XL at clipdrop.co to generate a patty / burguer / hamburguer meat images, but it looks like it's impossible. I've tried dozens of prompts and the result is always a complete hamburguer. You can check the last two prompts I tested bellow and I'd really appreciate if you could give me some advice on what I can improve in this prompts to get closer to my desired result. Source: 6 months ago

• Stability AI releases its latest image-generating model, Stable Diffusion XL 1.0

  If you want to play around with Stable Diffusion XL: https://clipdrop.co. - Source: Hacker News / 11 months ago

• Just a general notice for the few people still hanging out here

  A lot of mis- and disinformation going on and it seems like it's getting worse fast. Fake people writing on reddit, fake portraits of people online https://www.thispersondoesnotexist.com/ (and that's already old tech), there are already pretty much fully convincing fake human voices in operation (on youtube videos etc.), there are fake people playing online video games and talking "into the mic" etc. Fully... Source: 11 months ago

• 230712 LE SSERAFIM Deskmat Concept

  Photoshop is not the best choice here. If you're new to design, better learn Figma. Adobe didn't pay $20 billion to acquire them for nothing, they know it's a better software. Photoshop is only useful in very specific cases, and even then the free browser version will likely be enough. Plus vector graphics are better in most cases anyway. I do everything for this subreddit in Figma + ClipDrop AI tools and I've... Source: 11 months ago

• SDXL 0.9 does not understand me. Well, at least not on my own machine.

  Hi, first time user of Stable Diffusion (and similar projects) here. I was playing around with SDXL 0.9 on clipdrop.co and wanted to dive a little bit deeper and so I installed SD.Next and downloaded SDXL 0.9. Well, lets say I am confused: I used the same prompt on clipdrop.co and locally, but the results are not even close. Can somebody point me in the right direction? I think I am missing something fundamental. Source: 11 months ago