Ruttl
Markup.io
Marker.io
Pastel
BugHerd
Userback
Usersnap
Fiidbakk
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
Figure Eight
To review fully developed websites, currently, people take screenshots, encircle design issues and share them in a word document or have long meetings with the developers to implement the changes. The average time required to review any page using such methods is over 3-4 hours alone, which makes such methods inefficient and time-consuming!
Thatโs why we built ruttl! Packed with powerful features, it allows users to add comments, edit content, track bugs, replace images, make design changes (& more) to web elements and share all kinds of changes needed to get implemented by developers. ruttl has streamlined the entire process of giving web design feedback and has become the favourite go-to design feedback tool for designers, developers, and agencies worldwide!
RuttlBased on our record, NumPy seems to be a lot more popular than Ruttl. While we know about 122 links to NumPy, we've tracked only 3 mentions of Ruttl. 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.
Competitors There are a few competitors out there that do something very similar (see https://ruttl.com/, https://usepastel.com/, https://bugherd.com/, https://www.markup.io/). This seems to suggest that there seems to be a general market for such a product. Source: over 3 years ago
Ruttl.com โ The best all-in-one feedback tool to collect digital feedback and review websites, PDF's and images. - Source: dev.to / over 3 years ago
Ruttl - Helps you leave comments directly on live websites. Source: almost 5 years ago
Unmatched integration with ML/AI ecosystems through NumPy, TensorFlow, and PyTorch. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
AI starts with math and coding. You donโt need a PhDโjust high school math like algebra and some geometry. Linear algebra (think matrices) and calculus (like slopes) help understand how AI models work. Python is the main language for AI, thanks to tools like TensorFlow and NumPy. If you know JavaScript from Vue.js, Pythonโs syntax is straightforward. - Source: dev.to / 11 months ago
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / over 1 year ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / almost 2 years ago
Markup.io - The easiest way to comment and share feedback on over 30 file types. Sign up for free, upload your content, drop a comment, and share for review. Yep, itโs that simple.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Marker.io - Visual feedback and bug reporting tool for websites
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Pastel - Sticky note-based feedback collection tool for live websites
OpenCV - OpenCV is the world's biggest computer vision library
