Scikit-learn VS Swift Playgrounds

Scikit-learn Reviews

Swift Playgrounds Reviews

1. Nathan    

   over 1 year ago
   Terrible online training course

   The lowest available rating score is 1, but if there were a zero, I would rate this program a zero. There are no pros to this programming course. The lessons are so brief that I cannot understand them. Before I gave up for good on this programming course, I was writing tons of messages to people on Youtube asking them to explain things to me, and I hated the constant hassle of having to write online messages asking for explanations for the simplest of things that the lessons did not explain. This programming course is NOT a do-it-yourself training course by any means --- and it should not be used by schoolteachers as student homework assignments, as I recently advised a 13-year-old who was having trouble with the lessons and nothing was being helpful to him. This training course should be accompanied not by brief and intelligible on-screen lessons, but it should be accompanied by a detailed high school-style textbook complete with images. By the way, I have Asperger's syndrome, I have all kinds of problems with learning and with executing tasks, and I cannot participate in gainful employment in ANY profession for this reason.

Scikit-learn mentions (27)

• 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: 12 months 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

• Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service

  This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago

Swift Playgrounds mentions (0)