Nanonets
Docsumo
DocParser
Amazon Textract
Rossum
Dashblock
Tesseract
Base64.ai
Google Cloud TPU
Scikit-learn
machine-learning in Python
Amazon Forecast
AWS Personalize
Qubole
python-recsys
BigML
NanoNets is a Deep Learning web platform that makes it easier than ever before to use Deep Learning in practical applications. It combines the convenience of a web-based platform with Deep Learning models to create image recognition and object classification applications for your business. You can easily build and integrate deep learning models using NanoNets’ API. You can also work with our pre-trained models which have been trained on huge datasets and return accurate results. NanoNets has leveraged recent advances in Deep Learning to build rich representations of data which are transferable across tasks. It’s as simple as uploading your input, generating the output and getting a functioning and highly accurate Deep Learning model for your AI needs. NanoNets is revolutionary because it allows you to train models without large datasets. With just 100 images you can train a model on our platform to detect features and classify images with a high degree of accuracy. NanoNets benefits you in four important ways: ● It reduces the amount of data needed to build a Deep Learning Model ● NanoNets handles the infrastructure for hosting and training the model, and for the run time ● It reduces the cost of running deep learning models by sharing infrastructure across models ● It is possible for anyone to build a deep learning model
Nanonets Google Cloud TPUNo Google Cloud TPU videos yet. You could help us improve this page by suggesting one.
Nanonets might be a bit more popular than Google Cloud TPU. We know about 6 links to it since March 2021 and only 5 links to Google Cloud TPU. 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.
Want to automate repetitive manual tasks? Check our Nanonets workflow-based document processing software. Source: almost 2 years ago
Nanonets is a no-code, workflow-based, and AI-enhanced intelligent document processing platform. It automates all document processes and is built on a robust, intelligent, self-learning OCR API that allows users to extract required data from documents in minutes. Source: almost 2 years ago
Check out our website here https://nanonets.com/ for more. We also have some free tools where you can experience our product for free (like https://nanonets.com/online-ocr). Source: almost 2 years ago
Here is another company, which I just came across by accident, which do the same: https://nanonets.com/. Source: about 2 years ago
We will be using Python3.6+, Django web framework, Nanonets for character extraction from an image, Cloudinary for image storage and Google Search API for performing the searches. - Source: dev.to / over 2 years ago
According to https://cloud.google.com/tpu, each individual TPUv3 has 420 Teraflops, and TPUv4 is supposed to double that performance, so if that guess is correct, it should take a few seconds to do inference. Quite impressive really. - Source: Hacker News / about 2 years ago
You can also rent a cloud TPU-v4 pod (https://cloud.google.com/tpu) which 4096 TPUv-4 chips with fast interconnect, amounting to around 1.1 exaflops of compute. It won't be cheap though (excess of 20M$/year I believe). - Source: Hacker News / over 2 years ago
Actually, that's done with TPUs which are more efficient: https://cloud.google.com/tpu. Source: almost 3 years ago
TPU training uses Google silicon and is thus a true deep learning alternative to Nvidia. Source: almost 3 years ago
The server choice really depends on how much CPU and RAM the requests take, how many users will be hitting the server, etc. You can start with a $5/month Digital Ocean server (or AWS or Google) and see if that works for you. Or you can outsource the server administration to Amazon or Google if you don't want to deal with it or need specialized tpu hardware. Source: about 3 years ago
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
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.
machine-learning in Python - Do you want to do machine learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python.
Amazon Textract - Easily extract text and data from virtually any document using Amazon Textract. Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables.
Amazon Forecast - Accurate time-series forecasting service, based on the same technology used at Amazon.com. No machine learning experience required.