February 21, 2020
Data science and data engineering are usually two different departments in organisations. Bridging the gap between the two is essential to success. Many times the brilliant applications created by data scientists don't find a match in production, just be...
February 7, 2020
Why so much silence? Building a company! That's why :) I am building pryml, a platform that allows data scientists build their applications on data they cannot get access to. This is the first of a series of episodes in which I will speak about the techn...
January 1, 2020
In the last episode of 2019 I speak with Filip Piekniewski about some of the most worth noting findings in AI and machine learning in 2019. As a matter of fact, the entire field of AI has been inflated by hype and claims that are hard to believe. A lot o...
December 28, 2019
This is the fourth and last episode of mini series "The dark side of AI". I am your host Francesco and I’m with Chiara Tonini from London. The title of today’s episode is Bias in the machine
C: Francesco, today we are starting with an infuriating ...
December 23, 2019
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Episode transcript
We always hear the word “metadata”, usually in a sentence that goes like this
Your Honor, ...
December 11, 2019
In 2017 a research group at the University of Washington did a study on the Black Lives Matter movement on Twitter. They constructed what they call a “shared audience graph” to analyse the different groups of audiences participating in the debate, and fo...
December 3, 2019
Chamath Palihapitiya, former Vice President of User Growth at Facebook, was giving a talk at Stanford University, when he said this: “I feel tremendous guilt. The short-term, dopamine-driven feedback loops that we have created are destroying how society ...
November 18, 2019
Generative Adversarial Networks or GANs are very powerful tools to generate data. However, training a GAN is not easy. More specifically, GANs suffer of three major issues such as instability of the training procedure, mode collapse and vanishing gradien...
November 12, 2019
What happens to a neural network trained with random data?
Are massive neural networks just lookup tables or do they truly learn something?
Today’s episode will be about memorisation and generalisation in deep learning, with Stanislaw Jastrzębski from ...
November 5, 2019
In this episode I speak with Jon Krohn, author of Deeplearning Illustrated a book that makes deep learning easier to grasp.
We also talk about some important guidelines to take into account whenever you implement a deep learning model, how to deal with ...
