#tex

https://github.com/fabiensanglard/gebbdoom

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https://github.com/andkret/Cookbook

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https://github.com/posquit0/Awesome-CV

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https://github.com/ixy-languages/ixy-languages

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https://github.com/rasbt/stat453-deep-learning-ss20

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https://github.com/soulmachine/machine-learning-cheat-sheet

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https://github.com/avehtari/BDA_course_Aalto

#tex #graphics #latex #pgf #tikz #tikz_figures

https://github.com/PetarV-/TikZ

#tex #biohackeu20 #hut23 #hut23_270 #hut23_396

https://github.com/alan-turing-institute/the-turing-way

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https://github.com/paulgp/applied-methods-phd

#tex #data_science #machine_learning #cheatsheet

https://github.com/aaronwangy/Data-Science-Cheatsheet

#tex #linux #kernel #linux_kernel #linux_kernel_module #linux_kernel_driver

https://github.com/sysprog21/lkmpg

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https://github.com/kenjihiranabe/The-Art-of-Linear-Algebra

#tex #algebra #category_theory #haskell_book #math

https://github.com/liuxinyu95/unplugged

#tex #exercises_solutions #machine_learning #mathematics

https://github.com/michaelgutmann/ml-pen-and-paper-exercises

#tex #latex #preprint

https://github.com/roaldarbol/LaPreprint

#tex #gpt_3 #gpt3 #llm #prompt_engineering #prompting

https://github.com/trigaten/Learn_Prompting

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This repository contains the source files for the book "Performance Analysis and Tuning on Modern CPU" by Denis Bakhvalov. The book is being updated for its second edition, and contributions from experts are welcome. You can help by writing sections, making small improvements, proposing new content, or reviewing the material. The book can be built into a PDF using specific tools like Python, Pandoc, and MiKTeX. The benefit to you is access to comprehensive knowledge on performance analysis and tuning from industry experts, and the opportunity to contribute and learn from others in the field.

https://github.com/dendibakh/perf-book

#tex #academic #academic_website #blog_engine #blogdown #digital_garden #hugo #hugo_academic #hugo_site #hugo_theme #netlify #obsidian #personal_website #portfolio_template #portfolio_website #resume_builder #resume_template #rmarkdown #roamresearch #rstudio #website_generation

The Hugo Academic CV Template helps you create a professional online resume and showcase your academic work easily. It's trusted by over 250,000 researchers and students. You can customize your site without needing to code using the Hugo Blox Builder. The template supports Markdown, LaTeX, and other formats for writing technical content. You can also import publications from BibTeX. This makes it easy to build a website that looks great on both mobile and desktop devices, helping you grow your audience and get more recognition for your work[1][3].

https://github.com/HugoBlox/theme-academic-cv

#tex #awesome #coverletter #cv #latex #latex_template #overleaf #pdf #resume #sharelatex #tex

Awesome CV is a LaTeX template designed for creating professional CVs, résumés, and cover letters with clean, customizable formatting, offering an easy way to produce polished job application documents that stand out. It includes pre-designed layouts, supports PDF generation, and works seamlessly with tools like Overleaf or Docker, saving time while ensuring a visually consistent and industry-standard presentation.

https://github.com/posquit0/Awesome-CV