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:
s someone who works remotely, I've tried my fair share of collaboration apps. However, I have to say that Microsoft Teams has impressed me the most. It's a comprehensive app that brings together all the tools I need to communicate and collaborate with my colleagues seamlessly.
The interface of Microsoft Teams is user-friendly and easy to navigate. I particularly love the left-hand navigation bar that provides quick access to all the features, including chats, meetings, files, and activity. The app integrates with other Microsoft apps, such as Outlook and OneDrive, making it easier to schedule meetings and access files. The chat feature is simple, yet effective, with options to create groups, share files, and use emojis and GIFs.
Based 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.
Slack - A messaging app for teams who see through the Earth!
Iterative.ai - Iterative removes friction from managing datasets and ML models and introduces seamless data scientists collaboration.
Airtable - Airtable works like a spreadsheet but gives you the power of a database to organize anything. Sign up for free.
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.
Creativity 365 - Cross-device content creation suite