AWS Chatbot
ML5.js
Nanonets
AWS CodeCommit
AWS CodePipeline
TensorFlow
Face Swap Live
Datadog
Algorithmia
Managed MLflow
neptune.ai
5Analytics
MCenter
Numericcal
Datatron
Iterative.ai
AWS Chatbot AlgorithmiaAWS Chatbot 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.
For visibility of the pipelines I have set up a NotificationTopic , this topic is a SNS Topic that has AWS ChatBot as a subscriber. Chatbot will then send the updates to my Slack workspace that I have set up. This way when the pipeline is triggered I will get the notifications on my phone and laptop. - Source: dev.to / 4 months ago
Setup AWS Chatbot for best experience to get notified directly on Slack and MS Teams. - Source: dev.to / 9 months ago
AWS Chatbot: Monitor, operate, and troubleshoot your AWS resources with interactive ChatOps. - Source: dev.to / about 1 year ago
Meet AWS Chatbot. Interactive agent that makes it easier to monitor and interact with your Amazon Web Services (AWS) resources from your team’s Slack channels. By integrating AWS Chatbot with Slack, DevOps teams can receive real-time notifications, view incident details, and response incident quickly without need to cycle among other tools. - Source: dev.to / over 1 year ago
Modern machine learning algorithms are basically pattern recognition machines. They can recognize patterns in speech and can create convincing variations of that speech. Modern chatbot programs have become widely available to the public over the last decade. It's easy for anyone with a few hundred bucks to buy AWS Chatbot time and some basic programming knowledge to create a chatbot that could post convincingly... Source: over 1 year 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 2 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 2 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 2 years ago
Seems similar to https://algorithmia.com. Source: over 2 years ago
Algorithmia.com — Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / almost 3 years ago
ML5.js - Friendly machine learning for the web
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.
Nanonets - Worlds best image recognition, object detection and OCR APIs. NanoNets’ platform makes it straightforward and fast to create highly accurate Deep Learning models.
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.
AWS CodeCommit - AWS CodeCommit is a fully-managed source control service that makes it easy for companies to host secure private Git repositories.
5Analytics - The 5Analytics AI platform enables you to use artificial intelligence to automate important commercial decisions and implement digital business models.
