This article explores how five of pharma’s biggest companies are applying (or attempting to apply) AI and machine learning to improve drug discovery.
When David Duvenaud, an AI researcher at the University of Toronto, discovered a major shortcoming in AI, he found a solution. See how he did it.
Learn how to influence marketing and sales decisions using a simple, yet powerful machine learning technique called K-means.
Learn about use cases where machine learning can be applied to insurance applications, including insurance advice to consumers and agents, claims processing, fraud protection, and risk management.
See the potential machine learning has for equity markets in portfolio management.
Check out the key areas where AI and machine learning are adding value for hospitals
See how firms are using machine learning in the alternative lending and funding landscape to curb fraud, get more complex insights into risk, make sounder funding decisions and achieve lower loss rates.
Check out this article that attempts to explain the terminology and delivery models adopted by public cloud providers. It aims to help business decision makers choose the right cloud-based ML and AI service.
Check out this presentation which is focussed on ML Systems at Spotify including less obvious pitfalls, which have caused troubles at Spotify. This talk assumes a certain level of familiarity with ML: You’ll get the most out of if you’ve some experience with applied ML, ideally on production systems.
See how banks are using AI for reconciliations, risk assessment, compliance, trading, customer service, and more.