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:
The people at iterative.ai are special.
Its hard to describe quickly, but if you're a potential client or employee--you could easily go your entire career unaware that groups like this exist.
Their tools (like DVC) are exceptional, but I write this review because one need only interact with the people there to understand why they're execptional.
The culture there is one that can only exist when the founding talent is top-tier. The experience you'll have, though, is so much more than that.
Recommend whole-heatedly.
Based on our record, Iterative.ai should be more popular than Activeloop. It has been mentiond 6 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: about 2 years ago
I'm Davit from Activeloop (activeloop.ai). Source: about 2 years ago
PyDrive2 is am open-source python package maintained by the awesome people at Iterative. And it is very easy to install:. - Source: dev.to / about 1 year ago
These three are made by Iterative.ai, and seem like very clean implementations of MLOps tooling - especially if you aren't dealing with massive data. https://iterative.ai/. Source: about 1 year ago
For what it's worth. (Full disclosure: I'm the community manager at Iterative (DVC,et.al.) Just wanted to make you aware of our online course (free) that we created specifically for Data Scientists (https://learn.iterative.ai). We know that bridging the gap between prototype to production/ jupyter notebook to reproducible/software engineering compatible, is a challenge. That's why we created the course. To also... Source: over 1 year ago
What do you think of iterative.ai tools like dvc or cml? I have no direct experience, but I am looking at setting up something similar to what you need for a personal project. Source: almost 2 years ago
Hey all, we (at iterative.ai) are launching TPI - Terraform Provider Iterative https://github.com/iterative/terraform-provider-iterative. Source: about 2 years ago
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