This Week in Machine Learning: DGM Models, Yeast, and Customer Retention

Posted May 6, 2020

To stay on top of the latest news in Data Science, AI, tech, and ML, you need to follow the trends and changes. To help you, we’ve picked top stories of the week.

Here goes a dose of the latest news, discoveries, and inspiring stories from the world of Machine Learning. There is something for everyone. Enjoy your read!

Weekly Roundup: April 27 – May 4

> Neptune.ai blog – make sure to visit our blog to find out interesting and in-depth articles on machine learning.

Also, we’ve recently launched a podcast so tune in and enjoy! 🎧

> Microsoft Research Unveils Three Efforts to Advance Deep Generative Models by Jesus Rodriguez | April 27

Microsoft Research efforts with Optimus, FQ-GAN and Prevalent present new ideas that can be incorporated into the new generation of DGM models. Microsoft Research open sourced the code related to this efforts together with the research papers.

> Applying Machine Learning to…..Yeast? on Google AI Blog | April 29

In collaboration with Calico Life Sciences, Google AI presents “Learning causal networks using inducible transcription factors and transcriptome-wide time series”, published in Molecular Systems Biology. Based on exhaustive experiments, they built a genome-wide model for the regulation of gene expression in S. cerevisiae and verified some of the results experimentally, enabling future investigations into less well understood biological systems. The Induction Dynamics gene Expression Atlas is available from Calico in a format easy to manipulate in python, with open-sourced code to do this on the Google Research GitHub. The data is hosted in a standard format at the Gene Expression Omnibus.

> How Machine Learning Can Help with Customer Retention by Euge Inzaugarat | April 30

In the article, the author writes about building a churn model to understand why customers are leaving.

> How A.I. may help solve science’s ‘reproducibility’ crisis by Jonathan Vanian on Fortune | May 4

Researchers often have trouble reproducing, or verifying, supposedly groundbreaking work described in scientific papers, raising questions about whether the findings in studies are genuine. Read about how AI can help.

> KDnuggets™ News of the week with top stories and tweets of the past week, plus opinions, tutorials, events, webinars, meetings, and jobs.

> Old but gold, the reliable Reddit thread on ML for more news on machine learning

That’s all folks! I hope you found something of interest in this weekly roundup. Don’t forget to check our blog for more inspiring articles.

👉 Came across an interesting ML article? Or maybe you wrote one yourself and would like to share it with other people? Let us know, we’ll spread the news in our weekly roundup!

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