One of the most compelling use cases of sentiment analysis today is brand awareness. If you can understand what people are saying about you in a natural context, you can work towards addressing key problems and improving your business processes. So how exactly can you get that up and running?
The Algorithmia marketplace makes it easy to extract the content you need from Twitter and pipe it into the right algorithms for sentiment analysis. There are a few algorithms on the platform for exploring different information from Twitter (like users, tweets, and followers), and a number for sentiment analysis.
Chatbots offer a useful way to leverage the power of AI, and are now accessible for any size of application. The back-and-forth written nature of chatting is conducive to utilizing existing chatbot frameworks and AI models to automate interactions which would have required a whole team of agents just a short time ago. To demonstrate how easy it is, we’ll use a chatbot framework and a sentiment analysis model from the Serverless AI Cloud — both of which have free trial tiers.
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When you share your carefully-curated content on social media, you want to ensure it reaches as much of your audience as possible. One important part of this process is picking an amazing image to include in that post. That’s why we created the Social Media Image Recommender, an algorithm which looks through your article’s text and images, and tells you which picture you should use when sharing your post on Facebook, Twitter, LinkedIn, or any other social network. As a bonus, it also smart-resizes your image to the correct size for social sharing, keeping the most important elements in the frame and discarding unimportant background, thanks to the magic of deep learning and machine vision.
Want to jump right in and try it out yourself? Check out our Image Recommender Demo! Like it? Sign up and integrate the Image Recommender Algorithm into your digital workflow to process thousands of articles every hour, and supercharge your content publishing pipeline!
When we implemented InceptionNet, a microservice to detect and label objects (features) in photos, we knew it would be helpful. Then, we built out VideoMetadataExtraction, a video pipeline which allows you to run feature-detection algorithms (and others) on an entire video. This allowed for some really powerful activities — like automatically scanning through home security footage to find all the cars of a specific make & model, or stripping out all the nudity-containing scenes of a movie to make a G-rated version.
Add emotion detection to your livestreaming service. Find all the faces in your security tapes. Detect the make and model of every car that passes your shop. Flag nudity in users’ uploaded videos.
These are just a few of the cool things you can do with our powerful Video Metadata Extraction microservice, which allows you to analyze an entire video with our many image data-extraction algorithms. But don’t simpy take our word for it — if you want to see how powerful this tool is, take a peek at our live demo: