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Finally, you can develop browser automation without the pain and the cost of deploying a fleet of headless browsers. Connect to BrowserCat, scale globally, and pay only for what you use. Scrape the web, automate your workflows, test your apps, generate beautiful images and pdfs from HTML, give you AI agent web access, and more.
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BrowserCat's answer
BrowserCat is built on robust open source technology that's under active development. The star of the show is Playwright, which is our recommended automation library. It's maintained by Microsoft, it officially supports JS, Python, Java, and .NET, and it's fast becoming the industry standard. BrowserCat also supports Puppeteer and numerous unofficial Playwright ports to Go, Rust, PHP, and Ruby.
BrowserCat's answer
Unlike other headless browser providers, BrowserCat gives you total control over your browser instances for as long as you need them. Leverage the browsers cache, cookies, and storage for bespoke browser automation jobs that truly differentiate your business from the competition.
BrowserCat's answer
In previous corporate and startup gigs, I faced the challenge of developing robust, fast, and scalable browser automation. Most APIs in the space are too limiting for our needs and they were often incredibly slow. On the other hand, hosting your own headless browser fleet was a pain. I founded BrowserCat to make scaling up browser automation as easy, reliable, and affordable as deploying a serverless function.
BrowserCat's answer
We primarily serve developers, whether the seek to develop unique browser automation jobs or radically improve the performance of their integration tests. However, we frequently work with management, biz ops, and product leaders to solve problems they can't solve any way but through automation.
BrowserCat's answer
BrowserCat is built for performance, scalability, stability, and affordability using modern web technologies. Many of our competitors were early to market and compete on entrenchment rather than functionality. Still others are bound by their existing users to continue supporting legacy tech, rather than embrace improved, modern standards. BrowserCat is focused on supporting your for the next ten years, rather than the past ten years.
Based on our record, Scikit-learn seems to be more popular. It has been mentiond 31 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.
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
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 / 11 months 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 / about 1 year 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 / almost 2 years ago
Microlink - Extract structured data from any website
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Apify - Apify is a web scraping and automation platform that can turn any website into an API.
OpenCV - OpenCV is the world's biggest computer vision library
Scrapy - Scrapy | A Fast and Powerful Scraping and Web Crawling Framework
NumPy - NumPy is the fundamental package for scientific computing with Python