RapidMiner
Scikit-learn
Dataiku
Pandas
NumPy
OpenCV
WEKA
Exploratory
SuperAnnotate
Labelbox
V7
CloudFactory
Hive
Dataloop AI
Playment
Supervisely
SuperAnnotate is the leading platform for building, fine-tuning, iterating, and managing your AI models faster with the highest-quality training data. With advanced annotation and QA tools, data curation, automation features, native integrations, and data governance, we enable enterprises to build datasets and successful ML pipelines. Partner with SuperAnnotate’s expert and professionally managed annotation workforce that can help you quickly deliver high-quality data for building top-performing models.
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Based on our record, RapidMiner should be more popular than SuperAnnotate. It has been mentiond 3 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.
RapidMiner: A data science platform that offers an automated EDA process, including data preprocessing, visualization, and analysis. Source: over 1 year ago
I hope this blog empowers you to start digging deeper into Apache Arrow and helps you to understand why we decided to invest in the future of Apache Arrow and its child products. I also hope it gives you the foundations to start exploring how you can build your own analytics applications from this framework. InfluxDB’s new storage engine emphasizes its commitment to the greater ecosystem. For instance, allowing... - Source: dev.to / over 1 year ago
Rapidminer - RapidMiner is a data science software platform developed by the company of the same name that provides an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics. Link - https://rapidminer.com/. - Source: dev.to / over 2 years ago
Ok, so I tried comparing 4 of the better data annotation tools like dLabel.org, CVAT.com, SuperAnnotate.com and Labelbox.com . I tried them all as thoroughly as I could and I probably missed some things so apologies in advance for that! Let me know what I missed in the comment. Btw, I'm Amir and I've worked most of my data-labeling career at dLabel.org. Source: about 3 years ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Labelbox - Build computer vision products for the real world
Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.
V7 - Pixel perfect image labeling for industrial, medical, and large scale dataset creation. Create ground truth 10 times faster.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
CloudFactory - Human-powered Data Processing for AI and Automation