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Welcome to Ariadve!
Get ready for Machine Learning and AI. Connect the dots in the Digital Age. Explore, research and share data intelligence. Stay in the lead. Add Machine Learning and AI as a key competence to your business. Let's travel together!
A pathway to Machine Learning that invests in personal skills, nourishes team growth and aims at business innovation by AI from within ...
We organize Machine Learning workflow as a pipeline that stages efficient & fault-tolerant programming, data driven machine learning, team & stake-holder knowledge transfer with continued data awareness, large audience AI application, and reversed business target feedback.
Deterministic programming provides the foundation for capturing, pruning, transforming and distributing data as a pre-condition to provide the necessary data input to Machine Learning, obtain its AI and get this AI applied. For compactness we label this process of deterministic programming as Data & Code.
With Machine Learning we move from deterministic to stochastic programming. It is important to label stochastic data as such and keep it separated from deterministic data. The successive process of Machine Learning distinguishes as Model & Train.
Use state-of-the-art functional programming for large scale data collection, light weight threading, message passing, resource efficient processing, fault tolerant supervision, network resilience, low maintenance and low latency data distribution as a necessary pre-condition for running distributed applications at scale.
Develop the machine learning data models, collect necessary data, train/retrain the models and adjust/enrich the data when and where necessary. Perform dataframe analysis of large data collections for better insight and representation. Get business feedback on true/false postives and negatives. Maintain the data science confusion matrix.
Share code & data knowledge, offer participation and build understanding beyond your own team. Instantly connect to a data scientist, UX/UI specialist, someone from marketing, IT database administrator, or any remote worker, stakeholder or even end-user. Get rid of scripts, manual steps, and outdated documents.
Web enable your AI application with Web server, Pub/Sub message server, low latency Web sockets, liveview Web page roundtrips and a database backend. Get ready for scale by using local application proxies with a local database replica that connects to its database master through a dedicated high speed IPv6 backbone.
Set out and don't be afraid to miss. Practise to close in. And learn to hit your AI goals! Ensure that Machine Learning train & test data reflects real world circumstance as its derived AI gets applied. Keep monitoring true/false positive and negative ratios. Revert them back as key Machine Learning pipeline metrics. Keep improving data precision and let AI positively impact business bottomline.