Presented by Vijay Pappu, Senior ML Engineering Manager, Personalization Lead at Peloton, this talk focuses on any ML systems that rely on a feedback loop for improvement. How do we measure the efficacy of an ML system?
In this sponsored article, Dmitry Dolgorukov, CRO and Co-Founder of HES FinTech, suggesets that to effectively combat fraud, microfinance institutions must establish robust fraud detection systems. Early detection and prevention of fraudulent activities are vital in minimizing financial impact and safeguarding the funds of vulnerable customers. Microfinance institutions face a significant menace in the form of fraudulent activities, endangering their provision of financial services to underserved communities. Fraud not only leads to substantial financial losses but also erodes trust in the system, impeding the mission of microfinance institutions to foster inclusive growth and alleviate poverty.
This white paper from Dell Technologies and AMD examines big data analytics projects in government and recommends 15 lessons government agencies can learn. Big data is big business, particularly in the government sector. According to market researchers at IDC, worldwide spending on big data and business analytics solutions grew 10.1% in 2021 to total an estimated $215.7 billion. And a lot of that spending came from the public sector as the government was among the top six industries for overall expenditures related to big data analytics.
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