Prisma VS Scikit-learn

Prisma Reviews

1. shah7

   | Admin at Lensa Mod | over 1 year ago
   Lensa

   Prisma AI is a computer vision and AI company that specializes in developing deep learning algorithms for image and video processing. It offers a range of products for object recognition, image and video classification, and style transfer. Many users have praised its ease of use and accurate results. However, like any technology, it has its limitations and may not always provide the best results for all use cases.

Scikit-learn Reviews

Prisma mentions (5)

• How would generating art in private work ?

  What if I just want to make a few? However if you're hoping to do this just for a few images then there are some very low cost apps (often free if you plan it right) which use Stable Diffusion and Dreambooth in the background to produce the personalised images. One such example is Lensa. Source: about 1 year ago

• Catching The Morning Sun

  Perhaps, or they just used an app like Prisma to add that “painting” effect. Source: about 2 years ago

• Need your review. As a backend dev are you happy with GraphQL vs REST?

  I had to deal with this more in Rails whereas in Node/Apollo, using Prisma made composing efficient/perform ant SQL queries trivial: https://www.prisma.io/. Source: over 2 years ago

• Carrack phone wallpaper edited using style transfer

  I really liked this wallpaper by /u/MadDaz and I tried using style transfers using prisma-ai.com to generate images a bit more abstract. Here are the results! Source: almost 3 years ago

• Rare Rye Rose Mash-up

  Thanks - I made it on my android phone using Prisma and Snapseed. Source: almost 3 years 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 / 2 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 / 11 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: 12 months 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