To fully realise the potential of AI and machine learning (ML), organisations must prioritise critical factors such as model selection, optimisation, monitoring, scalability, and the definition of success metrics. Incorporating AI and ML into business operations has become a critical priority for organisations aiming to remain competitive in a rapidly evolving landscape. However, for many organisations, harnessing the potential of these technologies in a meaningful way is still an unfulfilled reality. To address this challenge, I’ve examined some of the latest trends in MLops and developed actionable strategies that can help solve common ML engineering challenges. As you might expect,…
Yuval Fernbach
Yuval Fernbach
With over a decade of experience in data and machine learning, Yuval Fernbach is the co-founder and CTO of Qwak, leading the development of a fully managed ML platform that streamlines the entire machine learning lifecycle. Previously an ML Specialist at Amazon Web Services, Yuval has helped organisations design and deploy impactful machine learning solutions. Driven by a passion for innovation, Yuval specialises in leveraging data and technology to transform businesses.