Jupyter
Looker
Google BigQuery
Databricks
Presto DB
Rakam
Informatica
Concurrent
Iterative.ai
Algorithmia
Managed MLflow
neptune.ai
Spell
MCenter
Datatron
5Analytics
JupyterThe 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, Jupyter seems to be a lot more popular than Iterative.ai. While we know about 206 links to Jupyter, we've tracked only 6 mentions of Iterative.ai. 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.
Interesting, I would have guessed you had used something jupyter-like: https://jupyter.org/ https://explorabl.es/all/. - Source: Hacker News / 11 days ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / about 1 month ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / about 1 month ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / about 1 month ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 3 months 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: over 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: almost 2 years 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
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.
Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
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.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.