Tag: Technical
4 Key Takeaways from AI for Data-driven Insurers Webinar
The adoption of AI has increased exponentially across the business ecosystem in the past couple of years. Yet, Insurance still lags behind many industries due to the nature of its business. However, the ease of convenience that has come with AI implementations has made it indispensable to Insurers. So, where has the demand for the […]
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Bittrex vs Binance – Complete Crypto Exchange Comparison
Threekit unveils configurable AR for retail with ‘millions’ of customisations promised
ARK Price Jumps 48% After Binance’s Announcement
Bidao Review: Binance Chain Based DeFi Stablecoin
Will Gentler HIPAA Rules on Telehealth Now Protect Us From Breach Litigation Later?
Three from MIT awarded 2020 Guggenheim Fellowships
A game of Telephone: how accurate can translation really be?
Imagine sitting in a circle with a few people where each of you knows only two languages — one shared with the person on your left, and one shared with the person on your right. If you say something to the person on your right and ask them to pass on the message, it might …
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AI For Portfolio Management: From Markowitz To Reinforcement Learning
Artificial intelligence, machine learning, big data, and other buzzwords are disrupting decision making in almost any area of finance. On the back office, machine learning is widely applied to spot anomalies in execution logs, for risk management and fraudulent transaction detection. At the front office, AI is used for customer segmentation and support and pricing the derivatives. […]
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Prime XBT Review: Complete Exchange Overview
Entertainment during COVID-19: How esports is filling a void
Entertainment during COVID-19: How esports is filling a void
The debate over whether esports are “real sports” has been ongoing for years. But no one ever asked: what if esports are the only sports?
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The 5 Components Towards Building Production-Ready Machine Learning Systems
Introduction The biggest issue facing machine learning is how to put the system into production. Machine learning systems differ from traditional software in two fundamental ways: Machine learning is never fully deterministic; therefore, the performance of an ML system can’t be evaluated against a strict specification. Instead, it should always be evaluated against application-specific metrics (false […]
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