G'MIC Reviews

Scikit-learn Reviews

G'MIC mentions (34)

• Is there a 'Graphic Pen' filter or other grain-texture equivalent?

  But I would use G'MIC as you can scale the grain, control opacity Filters > G'MIC_Qt, a window opens Degradations > Add Grain > https://i.imgur.com/FHXJ6CF.jpg. Source: 6 months ago

• Is there really no way to edit all layers at once? Do I seriously have to make colour corrections on every single individual layer?

  G'MIC will do it, On the GIMP top menu go to Filters > G'MIC_Qt, do your color correction and then at the bottom on the input select "All" or "All visible" or whatnot (multiple option). Source: 12 months ago

• The map reveals a lot of clues?

  This is just GMIC filters which are an awesome free filter suite for Photoshop/Gimp/Krita. Source: about 1 year ago

• Yet another GIMP newbie with a question: Am I barking up the right tree?

  You do not need to abandon the ship, with 2 plugins (one is G'MIC, the other one is to export layers as image and it does way more as well), and a one line code in terminal, you will be able to do it with GIMP (although I think it's the perfect job for ImageMagick, but I don't master it). Source: about 1 year ago

• How would you go about combining 75,000 images into a single image (more details inside post)

  With a plugin, GMIC you can also produce the average layer, so that spares you setting all the opacities. You still have to load them in Gimp (not too likely to have hem all fit and display). You can also use GMIC directly in a command line (but again, a command line with 75000 files is not obvious, so you may also have to divide and conquer). Source: about 1 year ago

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: about 1 year ago