Based on our record, Laravel should be more popular than Scikit-learn. It has been mentiond 194 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.
Laravel is a popular PHP framework known for its expressive syntax and rich ecosystem of features. Here's why it shines for building RESTful APIs:. - Source: dev.to / 26 days ago
Implementation In this article, we'll delve into the concept of rate limiting in Laravel; a popular PHP framework. We will explore how to set it up, customize it to suit your application's needs, and handle common scenarios. By the end, you'll have the knowledge and confidence to implement rate limiting in your Laravel applications, enhancing their security and stability. - Source: dev.to / about 2 months ago
Delving into PHP frameworks like Laravel or Symfony is like building a skyscraper, with Composer acting as your "construction foreman," guiding you step by step to ensure your code is robust and awe-inspiring. This stage involves getting familiar with popular PHP frameworks such as Laravel, Symfony, CodeIgniter, etc., and utilizing the functionalities provided by these frameworks to rapidly develop efficient,... - Source: dev.to / about 2 months ago
Your very first starting point should be the Laravel documentation. Known for its clear explanations and user-friendly layout, the Laravel documentation makes setup a breeze, ensuring you get off to the best possible start. - Source: dev.to / about 2 months ago
In this tutorial, we will learn how to create a GraphQL API with Laravel, a popular PHP web framework. We will be creating a simple student model, seeding the database with dummy data, setting up a database connection, and creating a GraphQL server by defining our API's schema, queries, and mutations. We’ll also learn how to make requests to our API (test our endpoints) using a tool like Insomnia or Postman. By... - Source: dev.to / 3 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 / 11 months 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: 12 months 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: 12 months ago
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
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
Django - The Web framework for perfectionists with deadlines
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
CodeIgniter - A Fully Baked PHP Framework
OpenCV - OpenCV is the world's biggest computer vision library
Ruby on Rails - Ruby on Rails is an open source full-stack web application framework for the Ruby programming...
NumPy - NumPy is the fundamental package for scientific computing with Python