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@ -3,7 +3,7 @@
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<div align="center" markdown="1">
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[](https://github.com/sindresorhus/awesome) 
|
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[](https://creativecommons.org/licenses/by/4.0/) 
|
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[](https://creativecommons.org/licenses/by/4.0/) 
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[](https://github.com/EbookFoundation/free-programming-books/pulls?q=is%3Apr+is%3Amerged+created%3A2025-10-01..2025-10-31)
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</div>
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@ -2696,6 +2696,7 @@ Books on general-purpose programming that don't focus on a specific language are
|
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### Web Services
|
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* [Pro Web 2.0 Mashups: Remixing Data and Web Services (2008)](https://mashupguide.net/1.0/html/) - Raymond Yee (HTML) (CC BY-NC-SA)
|
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* [RESTful Web Services](http://restfulwebapis.org/RESTful_Web_Services.pdf) (PDF)
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@ -418,6 +418,7 @@
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* [Curso de Python e Django](https://osantana.me/curso-de-python-e-django)
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* [Django 101 - Introdução ao Django](http://turing.com.br/material/acpython/mod3/django/index.html)
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* [Introdução a Visão Computacional com Python e OpenCV](http://professor.luzerna.ifc.edu.br/ricardo-antonello/wp-content/uploads/sites/8/2017/02/Livro-Introdu%C3%A7%C3%A3o-a-Vis%C3%A3o-Computacional-com-Python-e-OpenCV-3.pdf) (PDF)
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* [Introdução ao Python](https://files.cercomp.ufg.br/weby/up/688/o/M2_IP_24-09-24.pdf) - Rafael Divino Ferreira Feitosa (PDF)
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* [O Guia do Mochileiro para Python!](https://python-guide-pt-br.readthedocs.io/pt_BR/latest/)
|
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* [O tutorial de Python](http://turing.com.br/pydoc/2.7/tutorial/)
|
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* [Pensando Tkinter](https://www.dcc.ufrj.br/~fabiom/mab225/PensandoTkinter.pdf) - Steven Ferg (PDF)
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@ -149,12 +149,16 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
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* [Generative AI in Higher Education: The ChatGPT Effect](https://www.taylorfrancis.com/books/oa-mono/10.4324/9781003459026/generative-ai-higher-education-cecilia-ka-yuk-chan-tom-colloton) - Cecilia Ka Yuk Chan, Tom Colloton (PDF) (CC BY)
|
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* [Getting Started with Artificial Intelligence , 2nd Edition](https://www.ibm.com/downloads/cas/OJ6WX73V) - Tom Markiewicz, Josh Zheng (PDF)
|
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* [Graph Representational Learning Book](https://www.cs.mcgill.ca/~wlh/grl_book/) - William L. Hamilton
|
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* [How Transformer LLMs Work](https://www.deeplearning.ai/short-courses/how-transformer-llms-work/) - Jay Alammar, Maarten Grootendorst (DeepLearning.AI)
|
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* [Hugging Face LLM Course](https://huggingface.co/learn/llm-course/en/chapter1/1) (HTML)
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* [Introduction to Autonomous Robots](https://github.com/correll/Introduction-to-Autonomous-Robots/releases) - Nikolaus Correll (PDF) (CC BY-NC-ND)
|
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* [Large Language Models from Scratch](https://www.youtube.com/watch?v=lnA9DMvHtfI) - freeCodeCamp (YouTube)
|
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* [Machine Learning For Dummies®, IBM Limited Edition](https://www.ibm.com/downloads/cas/GB8ZMQZ3) - Daniel Kirsch, Judith Hurwitz (PDF)
|
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* [Mastering Generative AI and Prompt Engineering: A Practical Guide for Data Scientists](https://datasciencehorizons.com/pub/Mastering_Generative_AI_Prompt_Engineering_Data_Science_Horizons_v2.pdf) - Data Science Horizons (PDF)
|
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* [On the Path to AI: Law’s prophecies and the conceptual foundations of the machine learning age](https://link.springer.com/book/10.1007/978-3-030-43582-0) - Thomas D. Grant, Damon J. Wischik (PDF, EPUB)
|
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* [Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp](https://github.com/norvig/paip-lisp) - Peter Norvig
|
||||
* [Probabilistic Programming & Bayesian Methods for Hackers](https://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) - Cam Davidson-Pilon (HTML, Jupyter Notebook)
|
||||
* [Stanford CS224N: Natural Language Processing with Deep Learning](https://www.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ) - Christopher Manning (Stanford Online)
|
||||
* [The History of Artificial Intelligence](https://courses.cs.washington.edu/courses/csep590/06au/projects/history-ai.pdf) - Chris Smith, Brian McGuire, Ting Huang, Gary Yang (PDF)
|
||||
* [The Quest for Artificial Intelligence: A History of Ideas and Achievements](https://ai.stanford.edu/~nilsson/QAI/qai.pdf) - Nils J. Nilsson (PDF)
|
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|
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@ -279,8 +283,9 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
|
||||
* [A Programmer's Guide to Data Mining](http://guidetodatamining.com) - Ron Zacharski (Draft)
|
||||
* [Data Jujitsu: The Art of Turning Data into Product](http://www.oreilly.com/data/free/data-jujitsu.csp) (email address *requested*, not required)
|
||||
* [Data Mining Algorithms In R](https://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R) - Wikibooks
|
||||
* [Data Mining Concepts and Techniques](https://ia800702.us.archive.org/7/items/datamining_201811/DS-book%20u5.pdf) - Jiawei Han, Micheline Kamber, Jian Pei (PDF) ( :card_file_box: archived)
|
||||
* [Data Mining Concepts and Techniques](https://ia800702.us.archive.org/7/items/datamining_201811/DS-book%20u5.pdf) - Jiawei Han, Micheline Kamber, Jian Pei (PDF) *( :card_file_box: archived)*
|
||||
* [Data Science at the Command Line](https://datascienceatthecommandline.com/2e/) - Jeroen Janssens
|
||||
* [Data Science with Python](https://www.youtube.com/watch?v=LHBE6Q9XlzI) - freeCodeCamp
|
||||
* [Elements of Data Science](https://allendowney.github.io/ElementsOfDataScience/README.html) - Allen B. Downey
|
||||
* [Feature Engineering and Selection: A Practical Approach for Predictive Models](https://bookdown.org/max/FES/) - Max Kuhn, Kjell Johnson
|
||||
* [Foundations of Data Science](https://www.cs.cornell.edu/jeh/book.pdf) - Avrim Blum, John Hopcroft, Ravindran Kannan (PDF)
|
||||
@ -288,11 +293,13 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
|
||||
* [Hands-On Data Visualization](https://handsondataviz.org) - Jack Dougherty, Ilya Ilyankou (HTML)
|
||||
* [High-Dimensional Data Analysis with Low-Dimensional Models: Principles, Computation, and Applications](https://book-wright-ma.github.io/Book-WM-20210422.pdf) - John Wright, Yi Ma (PDF)
|
||||
* [Internet Advertising: An Interplay among Advertisers, Online Publishers, Ad Exchanges and Web Users](https://arxiv.org/pdf/1206.1754v2.pdf) (PDF)
|
||||
* [Introduction to Cultural Analytics & Python](https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html) - Melanie Walsh
|
||||
* [Introduction to Cultural Analytics & Python](https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html) - Melanie Walsh
|
||||
* [Introduction to Data Science](https://docs.google.com/file/d/0B6iefdnF22XQeVZDSkxjZ0Z5VUE/edit?pli=1) - Jeffrey Stanton
|
||||
* [Introduction to Data Science in Python](https://www.coursera.org/learn/python-data-analysis) - Christopher Brooks (University of Michigan) (Coursera)
|
||||
* [Julia Data Science](https://juliadatascience.io) - Jose Storopoli, Rik Huijzer, Lazaro Alonso (HTML) (CC BY-NC-SA 4.0)
|
||||
* [Mining of Massive Datasets](http://infolab.stanford.edu/~ullman/mmds/book.pdf) - Jure Leskovec, Anand Rajaraman, Jeffrey D. Ullman (PDF)
|
||||
* [Probability and Statistics with Examples using R](https://www.isibang.ac.in/~athreya/psweur/index.html#usage) - Siva Athreya, Deepayan Sarkar, Steve Tanner (HTML) ( :construction: *in process*)
|
||||
* [Probability and Statistics with Examples using R](https://www.isibang.ac.in/~athreya/psweur/index.html#usage) - Siva Athreya, Deepayan Sarkar, Steve Tanner (HTML) *( :construction: *in process*)*
|
||||
* [Python for Data Science – Hands-on Projects](https://www.youtube.com/watch?v=vaMMLLf0wLM) - LunarTech (freeCodeCamp) (YouTube)
|
||||
* [School of Data Handbook](https://schoolofdata.org/handbook/)
|
||||
* [Statistical inference for data science](https://leanpub.com/LittleInferenceBook/read) - Brian Caffo
|
||||
* [The Ultimate Guide to 12 Dimensionality Reduction Techniques (with Python codes)](https://www.analyticsvidhya.com/blog/2018/08/dimensionality-reduction-techniques-python/) - Pulkit Sharma
|
||||
@ -422,9 +429,11 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
|
||||
* [Approaching Almost Any Machine Learning Problem](https://github.com/abhishekkrthakur/approachingalmost) - Abhishek Thakur (PDF)
|
||||
* [Automated Machine Learning - Methods, Systems, Challenges](https://link.springer.com/book/10.1007/978-3-030-05318-5) - Frank Hutter, Lars Kotthoff, Joaquin Vanschoren (PDF, EPUB)
|
||||
* [Bayesian Reasoning and Machine Learning](http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage)
|
||||
* [CS50's Introduction to Artificial Intelligence with Python](https://cs50.harvard.edu/ai/) - David Malan (Harvard)
|
||||
* [Deep Learning](https://www.deeplearningbook.org) - Ian Goodfellow, Yoshua Bengio, Aaron Courville
|
||||
* [Deep Learning for Coders with Fastai and PyTorch](https://github.com/fastai/fastbook) - Jeremy Howard, Sylvain Gugger (Jupyter Notebooks)
|
||||
* [Dive into Deep Learning](https://d2l.ai)
|
||||
* [Elements of AI](https://www.elementsofai.com) - MinnaLearn, University of Helsinki
|
||||
* [Explorations in Parallel Distributed Processing: A Handbook of Models, Programs, and Exercises](https://web.stanford.edu/group/pdplab/pdphandbook) - James L. McClelland
|
||||
* [Foundations of Machine Learning, Second Edition](https://mitpress.ublish.com/ebook/foundations-of-machine-learning--2-preview/7093/Cover) - Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
|
||||
* [Free and Open Machine Learning](https://nocomplexity.com/documents/fossml/) - Maikel Mardjan (HTML)
|
||||
@ -439,6 +448,7 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
|
||||
* [Learn Tensorflow](https://bitbucket.org/hrojas/learn-tensorflow) - Jupyter Notebooks
|
||||
* [Learning Deep Architectures for AI](https://mila.quebec/wp-content/uploads/2019/08/TR1312.pdf) - Yoshua Bengio (PDF)
|
||||
* [Machine Learning](https://www.intechopen.com/books/machine_learning)
|
||||
* [Machine Learning Crash Course](https://developers.google.com/machine-learning/crash-course) - Google (HTML)
|
||||
* [Machine Learning for Beginners](https://github.com/Microsoft/ML-For-Beginners) - Microsoft
|
||||
* [Machine Learning for Data Streams](https://moa.cms.waikato.ac.nz/book-html/) - Albert Bifet, Ricard Gavaldà, Geoff Holmes, Bernhard Pfahringer
|
||||
* [Machine Learning from Scratch](https://dafriedman97.github.io/mlbook/) - Danny Friedman (HTML, PDF, Jupyter Book)
|
||||
@ -450,7 +460,7 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
|
||||
* [Neural Network Design (2nd Edition)](https://hagan.okstate.edu/NNDesign.pdf) - Martin T. Hagan, Howard B. Demuth, Mark H. Beale, Orlando De Jesús (PDF)
|
||||
* [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com)
|
||||
* [Pattern Recognition and Machine Learning](https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf) - Christopher M. Bishop (PDF)
|
||||
* [Patterns, Predictions, And Actions: A story about machine learning](https://mlstory.org/pdf/patterns.pdf) - Moritz Hardt, Benjamin Recht (PDF)
|
||||
* [Patterns, Predictions, And Actions: A story about machine learning](https://mlstory.org/pdf/patterns.pdf) - Moritz Hardt, Benjamin Recht (PDF)
|
||||
* [Practitioners guide to MLOps](https://services.google.com/fh/files/misc/practitioners_guide_to_mlops_whitepaper.pdf) - Khalid Samala, Jarek Kazmierczak, Donna Schut (PDF)
|
||||
* [Probabilistic Machine Learning - An Introduction](https://github.com/probml/pml-book/releases/latest/download/book1.pdf) - Kevin P. Murphy (PDF)
|
||||
* [Probabilistic Models in the Study of Language](https://idiom.ucsd.edu/~rlevy/pmsl_textbook/text.html) (Draft, with R code)
|
||||
@ -481,6 +491,7 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
|
||||
* [Analytic Geometry (1922)](http://djm.cc/library/Analytic_Geometry_Siceloff_Wentworth_Smith_edited.pdf) - Lewis Parker Siceloff, George Wentworth, David Eugene Smith (PDF)
|
||||
* [Applied Combinatorics](https://rellek.net/book/app-comb.html) - Mitchel T. Keller, William T. Trotter
|
||||
* [Applied Discrete Structures](https://faculty.uml.edu/klevasseur/ads2/) - Alan Doerr, Kenneth Levasseur
|
||||
* [Applied Quantitative Finance: Theory and Computational Tools](http://inis.jinr.ru/sl/M_Mathematics/MV_Probability/MVspf_Stochastics%20in%20finance/Haerdle%20et%20al.%20Applied%20Quantitative%20Finance%20(Springer)(423s).pdf) - Wolfgang K. Hardle, Nikolaus Hautsch, Ludger Overbeck (PDF)
|
||||
* [Basic Analysis: Introduction to Real Analysis](https://www.jirka.org/ra/) - Jiří Lebl
|
||||
* [Bayesian Methods for Hackers](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers) - Cameron Davidson-Pilon
|
||||
* [Book of Proof](https://www.people.vcu.edu/~rhammack/BookOfProof/) - Richard Hammack [(PDF)](https://www.people.vcu.edu/~rhammack/BookOfProof/Main.pdf)
|
||||
@ -507,6 +518,7 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
|
||||
* [Essentials of Metaheuristics](https://cs.gmu.edu/~sean/book/metaheuristics/) - Sean Luke
|
||||
* [Foundations of Combinatorics with Applications](https://www.math.ucsd.edu/~ebender/CombText/) - Edward A. Bender, S. Gill Williamson
|
||||
* [Foundations of Constructive Probability Theory](https://arxiv.org/pdf/1906.01803.pdf) - Yuen-Kwok Chan (PDF)
|
||||
* [Fundamentals of Quantitative Analysis](https://psyteachr.github.io/quant-fun-v3/) - Danielle Zhu (GitHub) (CC BY-SA)
|
||||
* [Geometry with an Introduction to Cosmic Topology](https://mphitchman.com) - Michael P. Hitchman
|
||||
* [Graph Theory](http://compalg.inf.elte.hu/~tony/Oktatas/TDK/FINAL/)
|
||||
* [Guide to Discrete Mathematics](https://core.ac.uk/download/pdf/326762636.pdf) - David Gries, Fred B. Schneider (PDF)
|
||||
|
||||
@ -54,6 +54,7 @@
|
||||
* [Domain-Driven Design](https://www.youtube.com/playlist?list=PLZVwXPbHD1KMsiA7ahRSbIwS3QMsQ0SbL) - Codely.TV (screencast)
|
||||
* [La Buhardilla Geek](https://www.ivoox.com/podcast-buhardilla-geek_sq_f1465450_1.html) - Juan Ángel Romero, Luis Miguel López (podcast)
|
||||
* [Maestría JS](https://anchor.fm/maestriajs) - Carlos Rojas (podcast) *(Última Actualización: Mayo 2020)*
|
||||
* [Programador X](https://open.spotify.com/show/6iuwL4j3oyaMZyBThzv7Hq) - Xavier Reyes Ochoa (podcast)
|
||||
* [Programar es una Mierda](https://www.programaresunamierda.com) - Juan José Meroño Sanchez, Alexandre Ballesté Crevillén (podcast) *(Última Actualización: Junio 2020)*
|
||||
|
||||
|
||||
|
||||
@ -477,6 +477,7 @@
|
||||
|
||||
### Raspberry Pi
|
||||
|
||||
* [Curso de Raspberry Pi](https://www.youtube.com/playlist?list=PLx4x_zx8csUj1PvvXekoDwuUyL0pljiU1) - CFBCursos
|
||||
* [Curso de Raspberry Pi: primeiros passos](https://www.youtube.com/playlist?list=PLHz_AreHm4dnGZ_nudmN4rvyLk2fHFRzy) - Gustavo Guanabara
|
||||
|
||||
|
||||
@ -505,6 +506,8 @@
|
||||
### Sass
|
||||
|
||||
* [Curso de Sass](https://www.youtube.com/playlist?list=PLMy95_4XE08OmaSd_GOLKNkqhoJFvg7w7) - Vida FullStack
|
||||
* [Curso de SASS](https://www.youtube.com/playlist?list=PLEBYKM1xzmIPGBtBRU7aTqMZFbj2H3xqo) - BUSSOLA DEV
|
||||
* [Curso Sass](https://www.youtube.com/playlist?list=PL97KElaimHeGRtfkksKwxg6IGVZi_cR7J) - Amanda Vilela
|
||||
* [Sass placeholders: o jeito certo](https://www.udemy.com/course/sass-placeholders-o-jeito-certo/) - Tárcio Zemel (Udemy)
|
||||
|
||||
|
||||
@ -530,6 +533,7 @@
|
||||
### Swift
|
||||
|
||||
* [Aprendendo Swift do Iniciante ao Avançado. (Mac e Windows)](https://www.udemy.com/aprendendoswift3/) - Lucas Alencar (Udemy)
|
||||
* [Curso de introdução ao desenvolvimento iOS](https://www.youtube.com/playlist?list=PLprgbdnzrDkHjUr2mFq0ypg-v6RNChKA8) Attekita Dev
|
||||
* [Curso de Swift - Programação](https://www.youtube.com/playlist?list=PLJ0AcghBBWShgIH122uw7H9T9-NIaFpP-) - Tiago Aguiar
|
||||
* [Curso grátis Swift e SwiftUI](https://www.youtube.com/playlist?list=PLMdYygf53DP46rneFgJ7Ab6fJPcMvr8gC) - Filipe Deschamps
|
||||
|
||||
@ -575,4 +579,5 @@
|
||||
### SEO
|
||||
|
||||
* [Curso de SEO - Mão na massa](https://www.youtube.com/playlist?list=PLVPIs-7SxXA_O-fUH5PbKhEHdTPnYKMiE) - Flavio Klens (Agência Klens)
|
||||
* [Curso de SEO (Iniciante)](https://www.youtube.com/playlist?list=PLqDfVio-YDgtfPuoYe1Ps_y9Ds1RU444_) - Caio Rodrigues
|
||||
* [Curso prático de SEO](https://www.youtube.com/playlist?list=PLHz_AreHm4dm4pBTRvBFMpSXvEoymoa90) - Gustavo Guanabara (Curso em Video)
|
||||
|
||||
@ -1,7 +1,6 @@
|
||||
### Index
|
||||
|
||||
* [Angular](#angular)
|
||||
* [Ansible](#ansible)
|
||||
* [APL](#apl)
|
||||
* [Artificial Intelligence](#artificial-intelligence)
|
||||
* [C](#c)
|
||||
@ -12,7 +11,13 @@
|
||||
* [Dart](#dart)
|
||||
* [Data Science](#data-science)
|
||||
* [Data Structures and Algorithms](#data-structures-and-algorithms)
|
||||
* [Docker](#docker)
|
||||
* [DevOps](#devops)
|
||||
* [Ansible](#ansible)
|
||||
* [Chef](#chef)
|
||||
* [Docker](#docker)
|
||||
* [Jenkins](#jenkins)
|
||||
* [Kubernetes](#kubernetes)
|
||||
* [Puppet](#puppet)
|
||||
* [Git](#git)
|
||||
* [Go](#go)
|
||||
* [Graphs](#graphs)
|
||||
@ -31,7 +36,6 @@
|
||||
* [React.js](#reactjs)
|
||||
* [Vue.js](#vuejs)
|
||||
* [Kotlin](#kotlin)
|
||||
* [Kubernetes](#kubernetes)
|
||||
* [Language Translations](#language-translations)
|
||||
* [Latex](#latex)
|
||||
* [Machine Learning](#machine-learning)
|
||||
@ -75,15 +79,6 @@
|
||||
* [Angular Cheat Sheet – A Basic Guide to Angular](https://www.geeksforgeeks.org/angular-cheat-sheet-a-basic-guide-to-angular/) - GeeksforGeeks
|
||||
|
||||
|
||||
### Ansible
|
||||
|
||||
* [Ansible Basic Cheat Sheet](https://intellipaat.com/blog/tutorial/devops-tutorial/ansible-basic-cheat-sheet) - Intellipaat (HTML)
|
||||
* [Ansible Cheat Sheet](https://sites.google.com/site/mrxpalmeiras/ansible/ansible-cheat-sheet) - Mrxpalmeiras (HTML)
|
||||
* [Ansible Cheat Sheet — A DevOps Quick Start Guide](https://medium.com/edureka/ansible-cheat-sheet-guide-5fe615ad65c0) - edureka (HTML, PDF)
|
||||
* [Automate your tasks with this Ansible cheat sheet](https://opensource.com/article/20/11/ansible-cheat-sheet) - Opensource (HTML)
|
||||
* [How to Use Ansible: A Reference Guide](https://www.digitalocean.com/community/cheatsheets/how-to-use-ansible-cheat-sheet-guide) - DigitalOcean (HTML)
|
||||
|
||||
|
||||
### APL
|
||||
|
||||
* [A reference card for GNU APL](https://github.com/jpellegrini/gnu-apl-refcard/blob/master/aplcard.pdf) - jpellegrini (PDF)
|
||||
@ -160,8 +155,28 @@
|
||||
* [Data structures and algorithms study cheatsheets for coding interviews](https://www.techinterviewhandbook.org/algorithms/study-cheatsheet/)
|
||||
|
||||
|
||||
### Devops
|
||||
|
||||
* [Devops Cheat Sheet](https://cheatography.com/hapuchu/cheat-sheets/devops/) - hapachu (PDF)
|
||||
|
||||
|
||||
### Ansible
|
||||
|
||||
* [Ansible Basic Cheat Sheet](https://intellipaat.com/blog/tutorial/devops-tutorial/ansible-basic-cheat-sheet) - Intellipaat (HTML)
|
||||
* [Ansible Cheat Sheet](https://sites.google.com/site/mrxpalmeiras/ansible/ansible-cheat-sheet) - Mrxpalmeiras (HTML)
|
||||
* [Ansible Cheat Sheet — A DevOps Quick Start Guide](https://medium.com/edureka/ansible-cheat-sheet-guide-5fe615ad65c0) - edureka (HTML, PDF)
|
||||
* [Automate your tasks with this Ansible cheat sheet](https://opensource.com/article/20/11/ansible-cheat-sheet) - Opensource (HTML)
|
||||
* [How to Use Ansible: A Reference Guide](https://www.digitalocean.com/community/cheatsheets/how-to-use-ansible-cheat-sheet-guide) - DigitalOcean (HTML)
|
||||
|
||||
|
||||
### Chef
|
||||
|
||||
* [Chef Cheat Sheet](https://intellipaat.com/blog/tutorial/devops-tutorial/chef-cheat-sheet/) - Intellipaat (HTML)
|
||||
|
||||
|
||||
### Docker
|
||||
|
||||
* [Docker Cheat Sheet](https://github.com/SAYOUNCDR/Docker-CheetSheet/blob/main/docker-cheatsheet.md) - Sayoun Parui (Markdown)
|
||||
* [Docker Cheat Sheet](https://low-orbit.net/docker-cheat-sheet) - Anthony Rioux, Low Orbit Flux (HTML, PDF)
|
||||
* [Docker Cheat Sheet](https://web.archive.org/web/20220925022529/https://www.docker.com/wp-content/uploads/2022/03/docker-cheat-sheet.pdf) - Docker Inc., Solomon Hykes (PDF) *( :card_file_box: archived)*
|
||||
* [Docker Cheat Sheet](https://intellipaat.com/blog/tutorial/devops-tutorial/docker-cheat-sheet/) - IntelliPaat (HTML, PDF)
|
||||
@ -184,6 +199,24 @@
|
||||
* [The Ultimate Docker Cheat Sheet](https://dockerlabs.collabnix.com/docker/cheatsheet/) - Sangam Biradar, Collabnix DockerLabs (HTML)
|
||||
|
||||
|
||||
### Jenkins
|
||||
|
||||
* [Jenkins Cheat Sheet](https://intellipaat.com/blog/tutorial/devops-tutorial/jenkins-cheat-sheet/) - Intellipaat (HTML)
|
||||
|
||||
|
||||
### Kubernetes
|
||||
|
||||
* [Handy Cheat Sheet for Kubernetes Beginners](https://kubernetes.io/docs/reference/kubectl/cheatsheet/) - Kubernetes Documentation: kubectl Cheat Sheet (HTML)
|
||||
* [Kubernetes Cheat Sheet](https://www.mirantis.com/blog/kubernetes-cheat-sheet/) - Nick Chase (HTML)
|
||||
* [Kubernetes Cheat Sheet – 15 Kubectl Commands & Objects](https://spacelift.io/blog/kubernetes-cheat-sheet) - Spacelift (HTML)
|
||||
* [Kubernetes Cheat Sheet with KubeCtl](https://intellipaat.com/blog/tutorial/devops-tutorial/kubernetes-cheat-sheet/) - Intellipath (HTML)
|
||||
|
||||
|
||||
### Puppet
|
||||
|
||||
* [Puppet Cheat Sheet](https://intellipaat.com/blog/tutorial/devops-tutorial/puppet-cheat-sheet/) - Intellipaat (HTML)
|
||||
|
||||
|
||||
### Git
|
||||
|
||||
* [8 Easy Steps to Set Up Multiple GitHub Accounts \[cheat sheet included\]](https://blog.gitguardian.com/8-easy-steps-to-set-up-multiple-git-accounts/) - Thomas Segura, GitGuardian (HTML, PDF)
|
||||
@ -347,13 +380,6 @@
|
||||
* [Kotlin Cheatsheet and Quick Reference](https://koenig-media.raywenderlich.com/uploads/2019/11/RW-Kotlin-Cheatsheet-1.1.pdf) - Ray Wenderlich (PDF)
|
||||
|
||||
|
||||
### Kubernetes
|
||||
|
||||
* [Handy Cheat Sheet for Kubernetes Beginners](https://kubernetes.io/docs/reference/kubectl/cheatsheet/) - Kubernetes Documentation: kubectl Cheat Sheet (HTML)
|
||||
* [Kubernetes Cheat Sheet](https://www.mirantis.com/blog/kubernetes-cheat-sheet/) - Nick Chase (HTML)
|
||||
* [Kubernetes Cheat Sheet – 15 Kubectl Commands & Objects](https://spacelift.io/blog/kubernetes-cheat-sheet) - Spacelift (HTML)
|
||||
|
||||
|
||||
### Language Translations
|
||||
|
||||
* [Swift and C# Quick Reference - Language Equivalents and Code Examples](http://www.globalnerdy.com/wordpress/wp-content/uploads/2015/03/SwiftCSharpPoster.pdf) - Globalnerdy (PDF)
|
||||
|
||||
@ -131,6 +131,7 @@
|
||||
* [Data Science Tutorial for Beginners - Video Course](https://www.scaler.com/topics/course/python-for-data-science/) - course by Yash Sinha Scaler Topics
|
||||
* [Essential Linear Algebra for Data Science and Machine Learning](https://www.kdnuggets.com/2021/05/essential-linear-algebra-data-science-machine-learning.html) - KDnuggets
|
||||
* [Interactive Linear Algebra](https://textbooks.math.gatech.edu/ila/) - Dan Margalit, Joseph Rabinoff (HTML, PDF)
|
||||
* [LLM Transformer Model Visually Explained](https://poloclub.github.io/transformer-explainer/) - Georgia Tech (HTML)
|
||||
* [Top 10 Data Science Projects for Beginners - KDnuggets](https://www.kdnuggets.com/2021/06/top-10-data-science-projects-beginners.html)
|
||||
|
||||
|
||||
|
||||
@ -222,6 +222,7 @@
|
||||
* [Java Compiler](https://www.codinguru.online/compiler/java)
|
||||
* [JDoodle - Online Java Compiler Advanced IDE](https://www.jdoodle.com/online-java-compiler-ide/)
|
||||
* [JDoodle - Online Java Compiler IDE](https://www.jdoodle.com/online-java-compiler/)
|
||||
* [OneCompiler](https://onecompiler.com/java)
|
||||
* [Online Java Playground](https://labex.io/tutorials/java-online-java-playground-372914)
|
||||
* [OnlineGDB](https://www.onlinegdb.com/online_java_compiler)
|
||||
* [Programiz - Online Java Compiler](https://www.programiz.com/java-programming/online-compiler/)
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user