In this article, the author lays out the opportunities for artificial intelligence in healthcare and describes the pitfalls of classical disruption strategies.
Machine Learning
Article | “Business Intelligence in Banking – Current Applications”
Check out two ways in which AI-driven business intelligence software could bring value to banks and financial institutions, including investment firms: Report generation and predictive analytics.
Article | “Machine Learning Drug Discovery Applications – Pfizer, Roche, GSK, and More”
This article explores how five of pharma’s biggest companies are applying (or attempting to apply) AI and machine learning to improve drug discovery.
Article | “The Most Important Data Science Tool for Market and Customer Segmentation”
Learn how to influence marketing and sales decisions using a simple, yet powerful machine learning technique called K-means.
Article | “Machine Learning – Insurance Applications Use Cases”
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.
Article | “Machine Learning in Equity Markets”
See the potential machine learning has for equity markets in portfolio management.
Article | “3 Charts Show Where Artificial Intelligence is Making an Impact in Healthcare Right Now”
Check out the key areas where AI and machine learning are adding value for hospitals
Article | “Is Your Firm Ready for Machine Learning?”
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.
Article | “An Executive’s Guide To Understanding Cloud-based Machine Learning Services”
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.
Edu-Video | “Machine Learning Infra @ Spotify: Lessons learned”
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.