Iterative.ai
MCenter
neptune.ai
5Analytics
Managed MLflow
Spell
Datatron
Numericcal
Algorithmia
MCenter
5Analytics
neptune.ai
Spell
Managed MLflow
Datatron
Numericcal
Iterative.ai AlgorithmiaAlgorithmia is recommended for data scientists, machine learning engineers, and developers who need a flexible and scalable environment to deploy, manage, and share AI and machine learning models. It is particularly suitable for teams seeking to collaborate and leverage pre-built algorithms from a community-driven marketplace. Businesses looking to integrate machine learning capabilities into their operations without extensive infrastructure management will also benefit from Algorithmia's offerings.
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.
Iterative.ai might be a bit more popular than Algorithmia. We know about 6 links to it since March 2021 and only 5 links to Algorithmia. 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.
PyDrive2 is am open-source python package maintained by the awesome people at Iterative. And it is very easy to install:. - Source: dev.to / over 2 years 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 2 years 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 3 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 3 years ago
Hey all, we (at iterative.ai) are launching TPI - Terraform Provider Iterative https://github.com/iterative/terraform-provider-iterative. Source: about 3 years ago
To push a model into production, there are additional concerns which the tools in the versioning, deployment and release space aim to solve. This includes obtaining adequate infrastructure to run the model reliably and facilitating easy model release or rollback. Solutions in the MLOps space includes Kubeflow, Pachyderm and Algorithmia. - Source: dev.to / over 3 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 3 years ago
Algorithmia advertises themselves as an MLops platform for data scientists, and they provide an easy way to host models on a scalable REST API. Source: over 3 years ago
Seems similar to https://algorithmia.com. Source: over 3 years ago
Algorithmia.com — Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / almost 4 years ago
MCenter - Machine Learning Operationalization
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.
5Analytics - The 5Analytics AI platform enables you to use artificial intelligence to automate important commercial decisions and implement digital business models.
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.
Spell - Deep Learning and AI accessible to everyone
Datatron - Datatron automates the deployment, monitoring, governance, and validation of your machine learning models in scikit-learn, TensorFlow, Keras, Pytorch, R, H20 and SAS
