UserVoice Reviews

Amazon SageMaker Reviews

UserVoice mentions (8)

• YARWL (Yet Another Remarkable Wishlist)

  I have sent them some user stories, complete with storyboard images. I am not a beta participant though. I suggested that it would be helpful if they rolled out something like UserVoice's Feedback Manager, so there is transparency to what's in the request queue and where we users can formally vote on the value of a given feature suggestion. Source: over 1 year ago

• Ask HN: Could you please share which SaaS you are using for your SaaS?

  - Collecting customer's feature requests: This is a tough one, I am using https://uservoice.com/ but I don't like it that much. I am searching for a self-hosted alternative to https://canny.io/. - Source: Hacker News / over 2 years ago

• "Help us to improve your reMarkable experience"

  I think that RM should consider a solution such as UserVoice which will let the user community vote on what critical bug fixes or new features we feel are most important. Not only can a user upvote a feature request or critical fix, but they can also add comments to help substantiate their vote. Source: over 2 years ago

• How We Use Internal Hackathons to Create New Product Features

  Six months later, UserVoice wanted to sign in with Courier and mentioned we lacked some functionalities they wanted. Specifically, they wanted to put two blocks next to each other in the notification designer. So, the sales and product team reached out to me, and I went, “Oh yeah, I hacked that together; it was cool but with a few bugs.”. - Source: dev.to / over 2 years ago

• Move features requests from Reddit?

  Would having a proper Customer Feedback platform using something like Canny or UserVoice be useful? Source: over 2 years ago

Amazon SageMaker mentions (37)

• Quantum Convolutional Neural Networks

  Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. - Source: dev.to / 20 days ago

• Observations on MLOps–A Fragmented Mosaic of Mismatched Expectations

  Damn straight. Oh, wait, some vendors have claimed to build an end-to-end solution. But, meh, that’s marketing talk. Take, for example, a well-known platform like Amazon Sagemaker, which describes itself as “a fully managed service that brings together a broad set of tools to enable high-performance, low-cost machine learning (ML) for any use case.” It’s a great platform. My startup has even partnered with them.... - Source: dev.to / about 2 months ago

• Sentiment Analysis with PubNub Functions and HuggingFace

  At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / 2 months ago

• Beginning the Journey into ML, AI and GenAI on AWS

  Generative Artificial Intelligence (GenAI) is a type of artificial intelligence that can generate text, images, or other media using generative models. AWS offers a range of services for building and scaling generative AI applications, including Amazon SageMaker, Amazon Rekognition, AWS DeepRacer, and Amazon Forecast. AWS has also invested in developing foundation models (FMs) for generative AI, which are... - Source: dev.to / 5 months ago

• Technical Architecture for LLMOps

  Amazon and Azure already have much of what you're talking about in AWS SageMaker and Azure MLOps. Source: about 1 year ago