Scikit-learn Reviews

Jasmine Reviews

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 / 20 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

Jasmine mentions (29)

• # 5 Testing Frameworks for JavaScript Developers

  Jasmine is renowned for its simplicity and is a popular choice for JavaScript testing. Here are its key features:. - Source: dev.to / about 1 month ago

• Migrating from Jest to Vitest for your React Application

  Vitest makes it effortless to migrate from Jest. It supports the same Jasmine like API. - Source: dev.to / 7 months ago

• Using Node.js for Automated Testing with Headless Browsers

  To execute your tests, you can create test scripts using popular testing frameworks like Mocha, Jasmine, or Jest. These frameworks provide a structured way to organize and run your tests, report results, and handle assertions. - Source: dev.to / 10 months ago

• Road Map To Become a Web Developer

  Testing frameworks like Jest, Mocha, and Jasmine are crucial for software development, ensuring code reliability and correctness. They offer features like test suites, test cases, assertions, and asynchronous testing support. - Source: dev.to / 12 months ago

• Naming Unit Tests Function

  The test framework used does matter for naming, because in some frameworks you'd use different naming conventions (i.e. The fluent naming used with https://jasmine.github.io/). Source: about 1 year ago