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aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
TranslatedChinese translation of 《Designing Data-Intensive Application》 (DDIA), 1st edition / 2nd edition
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
A free book that talks about design patterns/techniques used while developing with React.
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dmls-book`
These are the sample Bounded Contexts from the book "Implementing Domain-Driven Design" by Vaughn Vernon: http://vaughnvernon.co/?page_id=168
These are the sample Bounded Contexts for C#.NET from the book "Implementing Domain-Driven Design" by Vaughn Vernon: http://vaughnvernon.co/?page_id=168
The code repository for the prototypes included in the eBook "Inspired EHRs - Designing for Clinicians" (inspiredEHRs.gov). The code of the prototypes is made available under the Apache 2.0 open source license. This license agreement allows anyone to freely use the code and ideas presented in this book, subject to the conditions listed at http://opensource.org/licenses/Apache-2.0.