ConfigCat is a developer-centric feature flag service that helps you turn features on and off, change their configuration, and roll them out gradually to your users. It supports targeting users by attributes, percentage-based rollouts, and segmentation. Available for all major programming languages and frameworks. Can be licensed as a SaaS or self-hosted. GDPR and ISO 27001 compliant.
No features have been listed yet.
No ConfigCat videos yet. You could help us improve this page by suggesting one.
Based on our record, ConfigCat should be more popular than Scikit-learn. It has been mentiond 54 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
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 / 17 days ago
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
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
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
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
ConfigCat - ConfigCat is a developer-centric feature flag service with unlimited team size, excellent support, and a reasonable price tag. Free plan up to 10 flags, two environments, 1 product, and 5 Million requests per month. - Source: dev.to / 5 months ago
ConfigCat allows you to manage your feature flags from an easy-to-use dashboard, including the ability to set targeting rules for releasing features to a specific segment of users. These rules can be based on country, email, and custom identifiers such as age, eye color, etc. - Source: dev.to / 7 months ago
I recently started helping my friend @jordan-t-romero with a NextJS and NodeJS project she is working on. This weekend we incorporated ConfigCat so that we can add feature flags to control what content is displayed in the different environments (local, staging, production, etc.). - Source: dev.to / about 1 year ago
But how can you be sure you’re making the right changes? It’s impossible to read your clients’ minds, but A/B testing might just be the next best thing. In this article, I’ll guide you through conducting an A/B test on an Android (Kotlin) application using ConfigCat’s feature flag management system and Amplitude. - Source: dev.to / about 1 year ago
If you're planning on cutting back or saving bandwidth utilization and optimizing for better performance on the client side then a caching solution like Redis can help. And, as we've seen from the code examples, Redis integrates quite easily with ConfigCat. With a caching solution in place, you can supercharge the way you do standard feature releases, canary deployments, and A/B testing. Besides Node.js, ConfigCat... - Source: dev.to / about 1 year ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
LaunchDarkly - LaunchDarkly is a powerful development tool which allows software developers to roll out updates and new features.
OpenCV - OpenCV is the world's biggest computer vision library
Flagsmith - Flagsmith lets you manage feature flags and remote config across web, mobile and server side applications. Deliver true Continuous Integration. Get builds out faster. Control who has access to new features. We're Open Source.
NumPy - NumPy is the fundamental package for scientific computing with Python
Unleash - Open source Feature toggle/flag service. Helps developers decrease their time-to-market and to increase learning through experimentation.