4 out of 5 Data Scientists Agree

In the final episode of our Recommender Systems season, we explore the growing questions of trust, manipulation, privacy, fairness, sustainability, and user control. From fake reviews and shilling attacks to explainable recommendations and user-selected algorithms, we look at wha ...  Show more

In part two of the Data Skeptic Recommender Systems season finale, Kyle asks a deceptively difficult question: what should recommender systems actually optimize for? Drawing on conversations from across the season, the episode explores engagement, filter bubbles, popularity bias, ...  Show more

In this episode of the SuperDataScience Podcast, I chat with Eoin Murray, the founder of Kyso.io, a platform where you can blog about your data science projects using tools such as Jupyter notebooks. You will learn what the platform means for data scientists and how you can use i ...  Show more

See the full show notes for this episode on the website at talkpython.fm/467 

Welcome back to season two of My Career in Data – a DATAVERSITY Talks podcast where we sit down with professionals to discuss how they have built their careers around data.

This week we chat with Alyssa Lien, a Fraud Data Scientist at The Standard, about how she ...

<span style="font-weight: 400;">Hilary and Roger are back after a short break to discuss Roger's new job, the meaning of data science, and limited liability algorithms.</span>

<span style="font-weight: 400;">Show Notes:</span>

<a href="https://stat.utexa ...