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I am using the UWE Harvard CSL file to generate a bibliography from the following two citaitons:
@misc{fontanellaBeginnerGuideCustomer2022,
title = {A {{Beginner}}'s {{Guide}} to {{Customer Behavior Analysis}}},
author = {Fontanella, Clint},
year = {2022},
month = aug,
urldate = {2024-09-02},
journal = {HubSpot},
url = {https://blog.hubspot.com/service/customer-behavior-analysis}
}
@book{geronHandsonMachineLearning2020,
title = {Hands-on Machine Learning with {{Scikit-Learn}}, {{Keras}}, and {{TensorFlow}}: Concepts, Tools, and Techniques to Build Intelligent Systems},
shorttitle = {Hands-on Machine Learning with {{Scikit-Learn}}, {{Keras}}, and {{TensorFlow}}},
author = {G{\'e}ron, Aur{\'e}lien},
year = {2020},
edition = {7th Release. Second edition; updated for Tensor Flow2},
publisher = {O'Reilly},
address = {Beijing Boston Farnham Sebastopol Tokyo},
abstract = {Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks--Scikit-Learn and TensorFlow--author Aur{\'e}lien G{\'e}ron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets},
isbn = {978-1-4920-3261-8},
langid = {english}
}
I get wrongly-formatted citations when I do so:
Fontanella, C. (2022) A Beginner's Guide to Customer Behavior Analysis:director Trans.. August 2022 [online]. Available from: https://blog.hubspot.com/service/customer-behavior- analysis [Accessed 2 September 2024]
Géron, A. (2020) Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems:director Trans.. 7th Release. Second edition; updated for Tensor Flow2.. Beijing Boston Farnham Sebastopol Tokyo: O'Reilly.
Notice the wired "director Trans.." characters.
I tested the CSL with pandoc using a minimal markdown file and the citations are generated correctly:
Fontanella, C. (2022) A Beginner’s Guide to Customer Behavior Analysis Hub- Spot [online]. Available from: https://blog.hubspot.com/service/customer- behavior-analysis [Accessed 2 September 2024].
Géron, A. (2020) Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. 7th Release. Second edition; updated for Tensor Flow2. Beijing Boston Farnham
Sebastopol Tokyo: O’Reilly.
It would seem that there's a bug in the way Typst handles CSL files?
Reproduction URL
No response
Operating system
Mac OS
Typst version
typst 0.11.1
The text was updated successfully, but these errors were encountered:
Description
I am using the UWE Harvard CSL file to generate a bibliography from the following two citaitons:
I get wrongly-formatted citations when I do so:
Notice the wired "director Trans.." characters.
I tested the CSL with pandoc using a minimal markdown file and the citations are generated correctly:
It would seem that there's a bug in the way Typst handles CSL files?
Reproduction URL
No response
Operating system
Mac OS
Typst version
typst 0.11.1
The text was updated successfully, but these errors were encountered: