Участник:StasFomin/Bookmarks/Algorithms — различия между версиями

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=== 2024-01 ===
  
* 2024-01-18, 21:30:20: [https://github.com/codeninja55/mathematic_notebooks/tree/master codeninja55/mathematic_notebooks: A repository store for all mathematic references, jupyter notebooks, and notes from various courses taken.]
 
* 2024-01-18, 21:26:26: [https://github.com/juanklopper/Linear-algebra-for-data-science-with-python/tree/master juanklopper/Linear-algebra-for-data-science-with-python: Jupyter notebooks for my course on linear algebra using symbolic python.]
 
* 2024-01-18, 21:19:14: [https://github.com/Milwa97/A-level-math Milwa97/A-level-math: A level math course in form of jupyter notebooks. The aim of the course is to develop mathematical intuition and a better understanding of mathematics at the post-elementary level]
 
* 2024-01-18, 21:18:21: [https://github.com/aezarebski/aas-extended-examples aezarebski/aas-extended-examples: A collection of notebooks used in the tutorials for the applied analytic statistics course in 2020]
 
* 2024-01-18, 21:17:45: [https://github.com/raghurama123/NumericalMethods raghurama123/NumericalMethods: Contains Jupyter notebooks and other materials prepared for the course Numerical Methods offered at TIFR Hyderabad (https://moldis-group.github.io/teaching.html)]
 
* 2024-01-18, 21:16:47: [https://github.com/ymlai87416/ComputationalFinance_notebook ymlai87416/ComputationalFinance_notebook: Notebook and assignment for Coursera course: Introduction to Computational Finance and Financial Econometrics by Eric Zivot]
 
* 2024-01-18, 21:13:14: [https://github.com/Unipisa/HLT Unipisa/HLT: Notebooks for course HLT]
 
* 2024-01-18, 21:13:01: [https://github.com/Pengyue-Lab/uiuc-cs357-fa21-scripts Pengyue-Lab/uiuc-cs357-fa21-scripts: A repository of useful scripts for the course CS357 in the form of Jupyter Notebook.]
 
* 2024-01-18, 21:10:36: [https://github.com/inducer/numpde-notes inducer/numpde-notes: Slides/notes and Jupyter notebook demos for an introductory course of numerical methods for PDEs]
 
* 2024-01-18, 21:09:14: [https://github.com/iutzeler/NumericalOptimization/tree/master/Lab2_GradientDescent NumericalOptimization/Lab2_GradientDescent at master · iutzeler/NumericalOptimization]
 
* 2024-01-18, 21:05:56: [https://github.com/garth-wells/IA-maths-Jupyter/tree/master garth-wells/IA-maths-Jupyter: Notebooks in support of of the Part IA (Michaelmas Term) mathematics course at the Department of Engineering at University of Cambridge]
 
* 2024-01-18, 21:00:16: [https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming: Notebook for quick search]
 
* 2024-01-18, 20:58:40: [https://github.com/inducer/numerics-notes/tree/main inducer/numerics-notes: Slides/notes and Jupyter notebook demos for an introductory course of numerical analysis/scientific computing]
 
* 2024-01-18, 19:50:42: [https://github.com/croach/oreilly-matplotlib-course croach/oreilly-matplotlib-course: Jupyter notebooks from my O'Reilly Media course "Matplolib for Developers: Data Visualization and Analysis with Python"]
 
* 2024-01-18, 19:50:04: [https://github.com/z4ir3/finance-courses z4ir3/finance-courses: Notes and examples about Portfolio Construction and Analysis with Python (Jupyter notebooks)]
 
* 2024-01-18, 19:49:32: [https://github.com/jansenicus/www-coursera-downloader jansenicus/www-coursera-downloader: This Jupyter Notebook will help you downloading Coursera videos, subtitles and quizzes (but not answering the quiz). It will automatically download and convert vtt subtitle files into srt. All resources downloaded are numbered according to their sequence.]
 
* 2024-01-18, 19:48:16: [https://github.com/fastai/numerical-linear-algebra-v2 fastai/numerical-linear-algebra-v2: Jupyter Notebooks for Computational Linear Algebra course, taught summer 2018 in USF MSDS program]
 
* 2024-01-18, 19:47:48: [https://github.com/yourwanghao/CMUComputationalPhotography yourwanghao/CMUComputationalPhotography: Jupyter Notebooks for CMU Computational Photography Course 15.463]
 
 
* 2024-01-18, 19:45:02: [https://github.com/lmarti/evolutionary-computation-course lmarti/evolutionary-computation-course: Jupyter/IPython notebooks about evolutionary computation.]
 
* 2024-01-18, 19:45:02: [https://github.com/lmarti/evolutionary-computation-course lmarti/evolutionary-computation-course: Jupyter/IPython notebooks about evolutionary computation.]
 
* 2024-01-18, 19:43:06: [https://github.com/mandli/intro-numerical-methods mandli/intro-numerical-methods: Jupyter notebooks and other materials developed for the Columbia course APMA 4300]
 
* 2024-01-18, 19:43:06: [https://github.com/mandli/intro-numerical-methods mandli/intro-numerical-methods: Jupyter notebooks and other materials developed for the Columbia course APMA 4300]
 
* 2024-01-17, 19:39:02: [https://github.com/ageron/tf2_course ageron/tf2_course: Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course]
 
* 2024-01-17, 19:39:02: [https://github.com/ageron/tf2_course ageron/tf2_course: Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course]
* 2024-01-17, 19:33:55: [https://github.com/fastai/numerical-linear-algebra fastai/numerical-linear-algebra: Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course]
 
 
* 2024-01-16, 07:43:24: [https://github.com/juanklopper/MIT_OCW_Linear_Algebra_18_06 juanklopper/MIT_OCW_Linear_Algebra_18_06: IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)]
 
* 2024-01-16, 07:43:24: [https://github.com/juanklopper/MIT_OCW_Linear_Algebra_18_06 juanklopper/MIT_OCW_Linear_Algebra_18_06: IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)]
 
* 2024-01-16, 07:43:04: [https://github.com/xuwenhao/geektime-ai-course xuwenhao/geektime-ai-course: Jupyter Notebooks for Geektime AI Course]
 
* 2024-01-16, 07:43:04: [https://github.com/xuwenhao/geektime-ai-course xuwenhao/geektime-ai-course: Jupyter Notebooks for Geektime AI Course]

Версия 00:47, 4 января 2025

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  • 2022-04-27, 22:04:58: Nick Titterton
    X = cvx.Variable((V, V), PSD=True)

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  • 2021-05-30, 11:24:30: Facebook
    Аллен Дауни прямо радует - читается хорошо, без академической воды и понятно, с адекватными и ясными примерами практических задач. Последний раз все было так ясно и лаконично при перерешивании задач по терверу из советского учебника Вентцель и книги по байесовским методам Джона Крушке. Покрутил, наверное, в 10 раз в голове теорему Байеса и, вообще, понятие вероятности, условной вероятности, совместной вероятности, априорного и апостериорного распределения, сопряженного приора, pdf, pmf, cdf с разных сторон (и в очередной раз так и не просек простую идею бета-распределения, но, верю, она же есть) - ну чтобы чуйка развилась еще больше. Я честно, от всего сердца и ума, делал несколько подходов к прикладной байесовской статистике с разных сторон и с разными инструментами, прочитал, наверно несколько книг (поняв в них далеко не все) и не помню уже как много статей, но постоянно преследовал вопрос - а зачем и как это мне поможет в повседневной практике? Основная цель, которую я преследовал и до сих пор преследую для себя - научиться понимать "небольшие" данные и причины, стоящие за ними глубже, чем позволяют популярные статистические методы и мало кем, на самом деле, глубоко понимаемые доверительные интервалы на хи-квадратах, погоняемых группами сТЬЮдентов

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