
Rossum
DocParser
Nanonets
Docsumo
Parseur.com
Veryfi
FlexiCapture
Klippa
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Rossum
MatplotlibBased on our record, Matplotlib seems to be a lot more popular than Rossum. While we know about 114 links to Matplotlib, we've tracked only 4 mentions of Rossum. 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.
Embrace the AI bubble: https://rossum.ai/ (I'm not affiliated). Source: about 3 years ago
Now my main point (no, not IBM cloud services !) An other way is desktop tool/cloud tool that are OCR dedicated to "formatted documents" like ROSSUM or KLIPPA and... (https://rossum.ai/, https://www.klippa.com/en/ocr/identity-documents/driving-licenses). The idea, if I remember well the business model, is like a lot of small companies need all to make OCR on the same type of documents you can pre-learn an IA then... Source: almost 4 years ago
You should check out https://rossum.ai/ I think their product fits your usecase. Source: almost 4 years ago
I have seen some site like https://rossum.ai/ and while I think it is very difficult is there a way to improve it like them ? Source: almost 5 years ago
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - 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
DocParser - Extract data from PDF files & automate your workflow with our reliable document parsing software. Convert PDF files to Excel, JSON or update apps with webhooks.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Nanonets - Worlds best image recognition, object detection and OCR APIs. NanoNetsโ platform makes it straightforward and fast to create highly accurate Deep Learning models.
NumPy - NumPy is the fundamental package for scientific computing with Python
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.