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Intelligent Data And Content Streams Using Machine Learning APIs

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We have been profiling a number of machine learning APIs lately, not because there is an opportunity to proxy and stream the APIs, but because of the possibilities around applying common machine learning models to the data and content streams our customers are producing. One of the interesting machine learning APIs we are profiling currently is called ParallelDots, which provide a suite of common, yet powerful machine learning models that anyone can integrate into their applications. As we profile the ParallelDots API, we are considering the possibilities for trickling, or streaming updates via the APIs our customer's are proxying using our service. Consider some of the opportunities for posting stream updates to any of the following APIs: - Sentiment - Sentiment API accepts input text, language code and API key to return a JSON response classifying the input text into a sentiment. API can extract this information from any type of text, web page or social media network.


Text Analysis Machine Learning APIs From Algorithmia

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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.


Quant Developers High Frequency Trading solutions on LinkedIn: "Artificial Intelligence and Deep Learning…

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Artificial Intelligence and Deep Learning is the next thing in HFT https://lnkd.in/eycwTgQ Key TakeawaysStreamdata.io was originally built for banks and brokers, but more recently hedge funds have begun using the service.Whilst Hedge Funds like Renaissance Technologies have been using mathematical appr


The Top-10 French Artificial Intelligence Startups - Nanalyze

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As France's youngest president at 40 years old, Emmanuel Macron is known for his strong handshake, boyish good looks, and his controversial method of selecting a mate. Recently, he set his sights on artificial intelligence, announcing a government program to invest $1.8 billion into AI over the next four years. The cornerstone of all this spending will be in the healthcare sector, where the aim is to make predictive and personalized care a reality using AI and big data. This prompted us to take a look at the ten most funded French AI startups according to Crunchbase. Founded in 2014, Shift Technology has raised $40 million to develop an AI-based insurance fraud detection service.