PMDS Podcast Polimi Data Scientists

Welcome to a new episode of "PMDS Pillz" by Polimi Data Scientists!

In this third pill, Antonio will guide us on a brief tour around deep learning state-of-the-art in finance and stock market prediction. We will try to understand whether Artificial Intelligence is intelligent enough to beat the market, foresee trends, and if it can help people and policymakers understand how to better allocate their money.

You can't miss it! 'Till next time, enjoy!

Hi PMDSer!

Welcome to a new episode of our podcast. Today we will be interviewing Théo Saulus, a young French researcher at Central Supelec who's currently working on graph machine learning applied to the biomedicine field.

He will help us understand how to find relevant cell structures and understand cancer development using graph neural networks.



Enjoy!

Welcome to a new episode of "PMDS Pillz" by Polimi Data Scientists!

In this second pill, Federico and Francesco take us on a brief tour around the concept of inductive biases, to discuss some insights about the role of problem knowledge in the design of a Machine Learning solution. We will see how some simple assumptions in the context translate into practical decisions that can greatly boost performance!

Mastering this concept gives us another precious key to open the black box of ML algorithms, you can't miss it!

'Till next time, enjoy!




Original soundtrack by Ania Limonta

Hi everyone! One aspect of the wide field of Data Science that is usually missed in that of the management of data throughout its life cycle. Good data management is what enables the Data Scientist to work without interruptions.

In today's episode we will be talking with Matteo Cimini, a Data Architect at Quantyca. He will guide us through the topic, explaining it as well as some of the current solutions for an efficient data management.

Moreover, we will also discuss where does the Data Scientist fit into the company ecosystem and how they can leverage solutions such as Quantyca's to amplify the impact of their work in the company.

Welcome to a new podcast series by Polimi Data Scientists!

In this first episode, we analyze the topic of the "Lottery Ticket Hypothesis". It is related to Neural Networks and focuses on the idea that it is possible to prune the weights of a Neural Network to obtain a subnetwork that can achieve performances similar to the entire network.In this way, the training expenses could be cut, saving money as well as time.

'Till next time, enjoy!

In today's episode we will talk with Stefano Restelli, a manager at Zalando, about programmatic advertising. We will learn how the right content is delivered to the right target at the right time with the aid of technology. We will start from the surface, understanding what marketing and programmatic advertising are, and then we will delve deeper into the connections between this discipline and Data Science and Artificial Intelligence.