LaunchDarkly might be a bit more popular than Amazon Rekognition. We know about 36 links to it since March 2021 and only 33 links to Amazon Rekognition. 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.
AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / about 1 month ago
I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 9 months ago
For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 10 months ago
Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / 12 months ago
Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year ago
Taplytics is a broad A/B testing platform for marketing teams. While DevCycle is a feature flagging tool built for developers. Taplytics actually has feature flagging, but DevCycle is much more focused and plans to compete directly with incumbents like LaunchDarkly by building a better developer experience (more on how later). But with Taplytics they built so many features and every customer was using them in a... - Source: dev.to / 4 months ago
I had a custom rule added to Little Snitch that blocked the following domains: launchdarkly.com, clientstream.launchdarkly.com, mobile.launchdarkly.com. Source: 5 months ago
There are however Saas to implement directly a feature management system. Several solutions exist like LaunchDarkly, Flagsmith or Unleash.io. Using a SaaS (Software as a Service) feature flagging solution offers the advantage of a faster and more straightforward implementation process. These services are readily available and can be quickly integrated into your project. - Source: dev.to / 8 months ago
Currently, there are numerous feature flag systems available. Options include our own company's open-source system, "Bucketeer", and the renowned SaaS "LaunchDarkly" among others. When comparing these, the following considerations might come into play:. - Source: dev.to / 8 months ago
A variety of tools can cover some of these use cases. PLG tools like Segment and journy.io can track activity. Maybe you use a feature flag service such as LaunchDarkly. Stripe or Chargebee might manage some of the billing-related aspects. Meanwhile, problems related to authentication might be visible in your Auth0 account. However, it’s unlikely that you’re using all these platforms. Even if you are, you probably... - Source: dev.to / 10 months ago
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