Activeloop
DoltHub
Iterative.ai
Looker
Managed MLflow
Domo
Pachyderm
DVC
Sisense
Looker
Tableau
Qlik
Domo
Microsoft Power BI
QlikSense
MicroStrategy
Activeloop provides an optimized format for unstructured data, so users can stream their machine learning datasets while training ML models in PyTorch and TensorFlow. Activeloop acts as a data lake for deep learning on unstructured data and offers in-browser dataset visualization, querying, and version control. On top of those features, Activeloop integrates with experimentation and labeling tools to allow rapid iteration on computer vision datasets.
Machine Learning teams can apply Activeloop's data infrastructure to ship their models fast in the following use cases:
Behind Sisense's drag-and-drop user interface and eye-grabbing visualization options lies a technology that forever changes the world of business analytics software. By removing limitations to data size and performance imposed by in-memory and relational databases, Sisense enables any business to deliver interactive terabyte-scale analytics to thousands of users within hours
Activeloop SisenseBased on our record, Activeloop seems to be more popular. It has been mentiond 4 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.
This repository contains two Python scripts that demonstrate how to create a chatbot using Streamlit, OpenAI GPT-3.5-turbo, and Activeloop's Deep Lake. The chatbot searches a dataset stored in Deep Lake to find relevant information and generates responses based on the user's input. Source: about 1 year ago
u/Remote_Cancel_7977 we just launched 100+ computer vision datasets via Activeloop Hub yesterday on r/ML (#1 post for the day!). Note: we do not intend to compete with HuggingFace (we're building the database for AI). Accessing computer vision datasets via Hub is much faster than via HuggingFace though, according to some third-party benchmarks. :). Source: about 2 years ago
Hub, our open-source package, lets you stream datasets while training to PyTorch/TensorFlow. Check out how we achieved 95% GPU utilization while training on ImageNet at 50% less cost. We're building the Database for AI, with everything it should contain. If there's an adjacent feature that would make it more useful for your workflow, do let us know! Source: over 2 years ago
I'm Davit from Activeloop (activeloop.ai). Source: over 2 years ago
DoltHub - DoltHub is where people collaboratively build, manage, and distribute structured data.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Iterative.ai - Iterative removes friction from managing datasets and ML models and introduces seamless data scientists collaboration.
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
Qlik - Qlik offers an Active Intelligence platform, delivering end-to-end, real-time data integration and analytics cloud solutions to close the gaps between data, insights, and action.
Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
