
Sign up to save your podcasts
Or


Sinisa Slijepcevic studied with Stephen Hawking, among other professors, while earning his PhD in applied mathematics at Cambridge University. Sinisa is a McK alum and independent consultant and runs a firm called Cantab Analytica, which is based in the UK and Croatia.
Sinisa's firm leverages machine learning to help clients make better decisions and to focus energy on the right decisions.
In our discussion, Sinisa provides several case examples to illustrate how machine learning can help make decisions in three ways:
First: decisions that may be subject to unconscious bias, such as the investment decisions made by venture capital firms
Second: decisions that are complex and also occur very frequently, such as dynamic pricing of hotel rooms.
Third: focusing management attention on the most important decisions, such as figuring out which purchasing decisions are the most critical in a supply chain.
You can learn more about Sinisa's firm on the website: cantab analytica.com
By Will Bachman4.9
7575 ratings
Sinisa Slijepcevic studied with Stephen Hawking, among other professors, while earning his PhD in applied mathematics at Cambridge University. Sinisa is a McK alum and independent consultant and runs a firm called Cantab Analytica, which is based in the UK and Croatia.
Sinisa's firm leverages machine learning to help clients make better decisions and to focus energy on the right decisions.
In our discussion, Sinisa provides several case examples to illustrate how machine learning can help make decisions in three ways:
First: decisions that may be subject to unconscious bias, such as the investment decisions made by venture capital firms
Second: decisions that are complex and also occur very frequently, such as dynamic pricing of hotel rooms.
Third: focusing management attention on the most important decisions, such as figuring out which purchasing decisions are the most critical in a supply chain.
You can learn more about Sinisa's firm on the website: cantab analytica.com

8,772 Listeners

1,956 Listeners

1,097 Listeners

171 Listeners

196 Listeners

225 Listeners

205 Listeners

173 Listeners

795 Listeners

10,015 Listeners

669 Listeners

8,786 Listeners

228 Listeners

636 Listeners

93 Listeners