PlanetScale Reviews

Scikit-learn Reviews

PlanetScale mentions (100)

• Good alternatives to Heroku

  Planetscale - Directly from their website: "PlanetScale is a MySQL-compatible serverless database that brings you scale, performance, and reliability — without sacrificing developer experience.". - Source: dev.to / about 1 month ago

• MySQL or Top Alternatives in 2024 and How to Choose One

  PlanetScale is a MySQL-compatible database that offers scale, performance, and reliability, and many more powerful database features. Leveraging cloud-native architecture, PlanetScale enables organizations to deploy, manage, and scale MySQL-compatible databases with ease. With features such as automatic sharding, distributed transactions, and high availability, PlanetScale enables businesses to handle large... - Source: dev.to / about 2 months ago

• Breaking the Myth: Scalable, Multi-Region, Low-Latency App Exists And Will Not Cost You A Kidney.

  For MySQL, we've got PlanetScale, and for PostgreSQL, there's Neon. - Source: dev.to / 3 months ago

• A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev

  Planetscale - PlanetScale is a MySQL-compatible, serverless database platform powered by Vitess, one database for free with 1 Production branch and 1 Development branch, 5GB storage, 1 Billion rows read/mo per database, and 10 Million rows written/mo per database. - Source: dev.to / 5 months ago

• Self-hosting Ghost with Docker and PlanetScale

  PlanetScale and Ghost were previously incompatible due to differences in their support for foreign key constraints. With PlanetScale now supporting foreign key constraints, a seamless collaboration between the two is achievable. Nonetheless, there remain minor incompatibilities that require resolution. - Source: dev.to / 6 months ago

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 / 18 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