麻豆AV

Artificial Intelligence innovation thrives in an environment where business arenas, fundamental research, and thought leadership overlap. As seen in recent AI initiatives in Montreal, determining the capacities of AI and related data analytics applications is essential to understanding how they will play out in the wider world, whether analyzing healthcare data or implementing predictive analytics in retail. On the Delve podcast, Desautels Professor Maxime Cohen demystifies how retailers can use data analytics to predict demand, make operational decisions, and boost revenue.

鈥淚t鈥檚 impossible for the human brain to process so much information and to find all the hidden patterns and correlations between different types of features in order to make accurate predictions,鈥� says Cohen. 鈥淭hat's why in the specific case of demand prediction in retail, machine learning algorithms are very useful and have been successfully applied to get very high prediction demands.鈥�

In his recent book, , published by Springer this year, Cohen and his co-authors (Paul-Emile Gras, Arthur Pentecoste and Renyu Zhang) provide a detailed guide for data scientists and students of business analytics. The book offers business insights to a wider audience as well, pointing to something essential for all retailers today: how to leverage their historical data to predict future demand for their products.

For more insights, listen to the full interview with Professor Maxime Cohen on the .

You can subscribe to the Delve podcast on , including and .

Bringing Insight to the Surface

Founded in 2019, Delve is the official thought leadership publication of 麻豆AV鈥檚 Desautels Faculty of Management. Under the direction of Professor Saku Mantere, inaugural Editor-in-Chief, Delve features the latest in management thinking that stretches perspectives, sparks new ideas, and brings clarity to decision-makers at all levels and across sectors.