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Based on our record, Scikit-learn should be more popular than Docsify.js. 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 / 12 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
I built a fast, responsive, and lightweight static documentation site powered by Docsify, hosted on AWS S3 with a CloudFront CDN for global distribution. The entire infrastructure is managed using Pulumi YAML, allowing me to declaratively define and deploy resources without writing any imperative code. - Source: dev.to / about 2 months ago
Okay new plan, does anyone know how to do this docsify on github? I obviously am a noob on github and recently on reddit. I'd like to help where I can but my knowlegde seems to be my handycap. I could provide you a trash-mail, if you need one, but I need a PO (product owner) to manage the git... I have no clue about this yet (pages and functions and stuff). Source: almost 2 years ago
Good idea. Instead of bookstack, I recommend something like Docsify The content is all in Markdown and can be managed in a git repo. Easy to deploy the whole website to any simple static HTTP server - or even Github pages. This way you can review contributions and have good version control. Source: almost 2 years ago
The tools to author it aren't that important, frankly. Ask your audience what they're most comfortable using and try to meet them there. If the stakeholders are technical, you have more options. If they aren't, I hope you like Google Docs or Word, because if you give them anything other than that or a PDF, they'll probably complain. At worst, yeah, write it in a long Markdown text file and use tools like pandoc to... - Source: Hacker News / over 2 years ago
Big fan of https://docsify.js.org since theres no need to compile your static site. A small amount of js just renders markdown. - Source: Hacker News / over 2 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
GitBook - Modern Publishing, Simply taking your books from ideas to finished, polished books.
OpenCV - OpenCV is the world's biggest computer vision library
Doxygen - Generate documentation from source code
NumPy - NumPy is the fundamental package for scientific computing with Python
Docusaurus - Easy to maintain open source documentation websites