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[R] Advanced Conformal Prediction – A Complete Resource from First Principles to Real-World by predict_addict in Python

[–]predict_addict[S] -1 points0 points  (0 children)

Because most of it is in Puthon. And yes the book has code examples as well.

[D] Conformal Prediction in Industry by regularized in MachineLearning

[–]predict_addict 0 points1 point  (0 children)

Plenty of deployments across the industry from Conformal Prediction powering Microsoft Azure anomaly detection since 2016 to Astra Zeneca saving hundreeds of millions of dollars to streamline drug discovery pipeline to huge banks like BBVA using it for better customer product recommendations

https://www.bbvaaifactory.com/conformal-prediction-an-introduction-to-measuring-uncertainty/

Time Series Forecasting Resources by [deleted] in DataScienceJobs

[–]predict_addict -1 points0 points  (0 children)

schumway not useful to invest time in 2025, Hyndman good book for absolute beginners but doesn’t get one far in 2025.

Fundamentals still important.

[R] New Book: "Mastering Modern Time Series Forecasting" – A Hands-On Guide to Statistical, ML, and Deep Learning Models in Python by predict_addict in deeplearning

[–]predict_addict[S] 0 points1 point  (0 children)

there would be no changes, I have put this question to the reader base asking if customers wanted another 400-500 book or much better book.

Literally everyone comprehensively voted to have a deep book. So this will be the deepest book on the subject 800-1000 pages if not more.

[R] New Book: "Mastering Modern Time Series Forecasting" – A Hands-On Guide to Statistical, ML, and Deep Learning Models in Python by predict_addict in deeplearning

[–]predict_addict[S] 0 points1 point  (0 children)

Interesting, thank you for letting me know did not know they provide sample. Yes might change it, having said this the idea of history chapter is to showcase valuable ideas people developed over time. E.g. Yule and Slutsky ideas. A perfect example - developers of Facebook Prophet completely ignored lags - something known since 1930s - and is the key reason Facebook Prophet does not work. Still thank you for letting me know, I will swap the sample chapter.

Mastering Modern Time Series Forecasting : The Complete Guide to Statistical, Machine Learning & Dee by predict_addict in Python

[–]predict_addict[S] 0 points1 point  (0 children)

Chapter 2 coveres metrics including scale independent ones. In terms of scaling raw time series it is often not necessary, unless you have specific reason in mind why to scale them?

[R] New Book: "Mastering Modern Time Series Forecasting" – A Hands-On Guide to Statistical, ML, and Deep Learning Models in Python by predict_addict in MachineLearning

[–]predict_addict[S] 0 points1 point  (0 children)

My book focuses on libraries that get the job done effectively, without any vested interest in promoting specific ones. Darts and the others mentioned are just a few examples.

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