DataRec Library for Reproducible in Recommend Systems

DataRec Library for Reproducible in Recommend Systems

In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich explores DataRec, a new Python library designed to bring reproducibility and standardization to recommender systems research. Guest Alberto Carlo Maria Mancino, a postdoc researcher from Politecnico di Bari, Italy, discusses the challenges of dataset management in recommendation research—from version control issues to preprocessing inconsistencies—and how DataRec provides automated downloads, checksum verification, and standardized filtering strategies for popular datasets like MovieLens, Last.fm, and Amazon reviews.

The conversation covers Alberto's research journey through knowledge graphs, graph-based recommenders, privacy considerations, and recommendation novelty. He explains why small modifications in datasets can significantly impact research outcomes, the importance of offline evaluation, and DataRec's vision as a lightweight library that integrates with existing frameworks rather than replacing them. Whether you're benchmarking new algorithms or exploring recommendation techniques, this episode offers practical insights into one of the most critical yet overlooked aspects of reproducible ML research.

Episoder(589)

N-Beats

N-Beats

Today on the show we have Boris Oreshkin @boreshkin, a Senior Research Scientist at Unity Technologies, who joins us today to talk about his work N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting. Works Mentioned: N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting By Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio https://arxiv.org/abs/1905.10437 Social Media Linkedin Twitter

12 Jul 202134min

Translation Automation

Translation Automation

Today we are back with another episode discussing AI in the work field. AI has, is, and will continue to facilitate the automation of work done by humans. Sometimes this may be an entire role. Other times it may automate a particular part of their role, scaling their effectiveness. Carl Stimson, a Freelance Japanese to English translator, comes on the show to talk about his work in translation and his perspective about how AI will change translation in the future.

6 Jul 202136min

Time Series at the Beach

Time Series at the Beach

Shane Ross, Professor of Aerospace and Ocean Engineering at Virginia Tech University, comes on today to talk about his work "Beach-level 24-hour forecasts of Florida red tide-induced respiratory irritation."

28 Jun 202123min

Automatic Identification of Outlier Galaxy Images

Automatic Identification of Outlier Galaxy Images

Lior Shamir, Associate Professor of Computer Science at Kansas University, joins us today to talk about the recent paper Automatic Identification of Outliers in Hubble Space Telescope Galaxy Images. Follow Lio on Twitter @shamir_lior

21 Jun 202136min

Do We Need Deep Learning in Time Series

Do We Need Deep Learning in Time Series

Shereen Elsayed and Daniela Thyssens, both are PhD Student at Hildesheim University in Germany, come on today to talk about the work "Do We Really Need Deep Learning Models for Time Series Forecasting?"

16 Jun 202129min

Detecting Drift

Detecting Drift

Sam Ackerman, Research Data Scientist at IBM Research Labs in Haifa, Israel, joins us today to talk about his work Detection of Data Drift and Outliers Affecting Machine Learning Model Performance Over Time. Check out Sam's IBM statistics/ML blog at: http://www.research.ibm.com/haifa/dept/vst/ML-QA.shtml

11 Jun 202127min

Darts Library for Time Series

Darts Library for Time Series

Julien Herzen, PhD graduate from EPFL in Switzerland, comes on today to talk about his work with Unit 8 and the development of the Python Library: Darts.

31 Mai 202125min

Forecasting Principles and Practice

Forecasting Principles and Practice

Welcome to Timeseries! Today's episode is an interview with Rob Hyndman, Professor of Statistics at Monash University in Australia, and author of Forecasting: Principles and Practices.

24 Mai 202131min

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