Helping us all make sense of, and enrich data that is moving along via our data pipes. It is common for our customers to perform sentiment analysis, enrich with tags, and extract names, dates, emails, and other relevant information for streams as they arrive, or as they are being delivered to other destinations. By adding additional tags, meaning, and other metadata, it makes it easier to connect and aggregate data across real-time streams, and transform existing streams into richer topical feeds. We are working on profiling, not just Algorithmia, but a number of other machine learning APIs. As we establish interesting collections of text analysis, deep learning, and other algorithms that can be applied to Streamdata.io streams, we'll publish here on the blog. If you have specific data and content, or machine learning model that you'd like to have delivered as part of your real-time infrastructure let us know. We are happy to prioritize specific types of data or profile more relevant machine learning APIs providers to help expedite your work. We are beginning to ramp up our efforts to profile relevant machine learning models, as the demand from our customers' increases, hoping to satisfy our customers demand for machine learning intelligence as they continue to optimize their streams of data across their organization.
Apr-8-2018, 23:56:26 GMT