Участник:StasFomin/Bookmarks/Algorithms — различия между версиями

Материал из DISCOPAL
Перейти к: навигация, поиск
(Добавлена закладка z4ir3/finance-courses: Notes and examples about Portfolio Construction and Analysis with Python (Jupyter notebooks))
(Добавлена закладка sheryl-ai/MVGCN: Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease (AMIA 2018))
(не показано 48 промежуточных версий этого же участника)
Строка 1: Строка 1:
 
== 2024 ==
 
== 2024 ==
 +
=== 2024-03 ===
 +
 +
* 2024-03-20, 19:14:22: [https://github.com/sheryl-ai/MVGCN sheryl-ai/MVGCN: Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease (AMIA 2018)]
 +
* 2024-03-03, 19:22:07: [https://sysblok.ru/knowhow/kak-ustroena-nejroset-bert-ot-google/ Как устроена нейросеть BERT от Google - Системный Блокъ]
 +
* 2024-03-03, 19:13:07: [https://github.com/LeorFinkelberg/Optimization LeorFinkelberg/Optimization]
 +
 +
=== 2024-02 ===
 +
 +
* 2024-02-27, 20:55:59: [https://vk.com/video-176869000_456239030 Video005 — Видео]
 +
 
=== 2024-01 ===
 
=== 2024-01 ===
  
 +
* 2024-01-27, 07:22:19: [https://github.com/MykolaHerasymovych/Optimizing-Acceptance-Threshold-in-Credit-Scoring-using-Reinforcement-Learning/blob/master/Source/simulation.py Optimizing-Acceptance-Threshold-in-Credit-Scoring-using-Reinforcement-Learning/Source/simulation.py at master · MykolaHerasymovych/Optimizing-Acceptance-Threshold-in-Credit-Scoring-using-Reinforcement-Learning]
 +
* 2024-01-27, 07:05:06: [https://habr.com/ru/companies/glowbyte/articles/519382/ ML и DS оттенки кредитного риск-менеджмента / Хабр]
 +
* 2024-01-27, 02:47:46: [https://bijournal.hse.ru/data/2015/10/12/1076342406/2.pdf BI 3 (33) 2015 new.indd - 2.pdf]
 +
* 2024-01-26, 03:06:01: [https://habr.com/ru/companies/yandex/articles/263991/ Вероятностное программирование / Хабр]
 +
* 2024-01-21, 03:00:34: [https://github.com/fast-algos/graphs-matrices-optimization/blob/master/lecture1.pdf graphs-matrices-optimization/lecture1.pdf at master · fast-algos/graphs-matrices-optimization]
 +
* 2024-01-21, 02:53:24: [https://github.com/ChrisTX/lecture-notes/tree/7726d59c6caeaa7ac874cbc1fb1e08353bfd98f3/Approximation%20Algorithms lecture-notes/Approximation Algorithms at 7726d59c6caeaa7ac874cbc1fb1e08353bfd98f3 · ChrisTX/lecture-notes]
 +
* 2024-01-20, 00:29:21: [https://github.com/tlkahn/zkSNARKs-Cryptography-Protocol-Survey tlkahn/zkSNARKs-Cryptography-Protocol-Survey]
 +
* 2024-01-20, 00:23:51: [https://github.com/prokls/theoretical-computer-science-2/blob/master/randomized_complexity_classes.pdf theoretical-computer-science-2/randomized_complexity_classes.pdf at master · prokls/theoretical-computer-science-2]
 +
* 2024-01-19, 23:12:56: [https://zhuanlan.zhihu.com/p/37270132 Теорема PCP, часть 1: Введение - Чжиху]
 +
* 2024-01-19, 23:07:56: [https://github.com/mourad1081/complexity-exam-questions mourad1081/complexity-exam-questions: Réponse aux questions de complexité]
 +
* 2024-01-19, 23:06:42: [https://github.com/LucaCappelletti94/lectures-notes/tree/0b0550ee36eab19d0d48f74e407beee1e5a3e78f/Unimi/Algoritmi%20e%20Complessita lectures-notes/Unimi/Algoritmi e Complessita at 0b0550ee36eab19d0d48f74e407beee1e5a3e78f · LucaCappelletti94/lectures-notes]
 +
* 2024-01-19, 22:51:02: [https://github.com/BrownAppliedCryptography/notes BrownAppliedCryptography/notes: Scribed course notes.]
 +
* 2024-01-19, 22:49:27: [https://github.com/mnielsen/expander_graph_notes mnielsen/expander_graph_notes: Notes on expander graphs]
 +
* 2024-01-19, 22:48:32: [https://github.com/pragmaticTNT pragmaticTNT]
 +
* 2024-01-19, 22:43:13: [https://github.com/mnielsen/expander_graph_notes/blob/193880dde69c1aa2bdf974a4975a0b960a278575/expanders_github.tex expander_graph_notes/expanders_github.tex at 193880dde69c1aa2bdf974a4975a0b960a278575 · mnielsen/expander_graph_notes]
 +
* 2024-01-19, 02:36:35: [https://github.com/sleepymalc/Notes/blob/7e28b1c548da109b7e89a62acc6ed1076841352c/EECS598-001-Approximation-Algorithms-and-Hardness-of-Approximation/Lectures/lec_2.tex Notes/EECS598-001-Approximation-Algorithms-and-Hardness-of-Approximation/Lectures/lec_2.tex at 7e28b1c548da109b7e89a62acc6ed1076841352c · sleepymalc/Notes]
 +
* 2024-01-19, 02:16:16: [https://github.com/sleepymalc/Notes/tree/7e28b1c548da109b7e89a62acc6ed1076841352c/EECS598-001-Approximation-Algorithms-and-Hardness-of-Approximation Notes/EECS598-001-Approximation-Algorithms-and-Hardness-of-Approximation at 7e28b1c548da109b7e89a62acc6ed1076841352c · sleepymalc/Notes]
 +
* 2024-01-19, 01:41:18: [https://github.com/arielgabizon/Lectures/blob/master/4elemproofAarhus2019.pdf Lectures/4elemproofAarhus2019.pdf at master · arielgabizon/Lectures]
 +
* 2024-01-19, 01:10:29: [https://github.com/Landarzar/complexityPoster/blob/master/poster.pdf complexityPoster/poster.pdf at master · Landarzar/complexityPoster]
 +
* 2024-01-19, 00:54:25: [https://github.com/jarrodmillman/pcp/blob/master/final.tex pcp/final.tex at master · jarrodmillman/pcp]
 +
* 2024-01-18, 22:17:49: [https://github.com/SanskarX10/Coding-Graph-Theory-101/tree/main SanskarX10/Coding-Graph-Theory-101: Coding and explanation of Graph theory algorithms used in computer science in python-3 . These set of notebooks acts as a course in graph theory.]
 +
* 2024-01-18, 22:16:14: [https://github.com/rjwrobel86/Python4Statistics/tree/main rjwrobel86/Python4Statistics: Python Scripts and Jupyter Notebooks for Prof. Robert Wrobel's Applied Business Statistics course at Webster University and anybody else who wants to learn!]
 +
* 2024-01-18, 22:04:34: [https://github.com/hishamcse/Discrete-Math-Specialization-Coursera-/tree/master hishamcse/Discrete-Math-Specialization-Coursera-: This repository contains the materials, python codes for the quiz and some codes implemented using jupyter notebook related to the specialization ( Introduction to Discrete Mathematics In Computer Science)]
 +
* 2024-01-18, 21:52:09: [https://github.com/i40a/python-for-industry40 i40a/python-for-industry40: Jupyter Notebook files from the course Python for Industry 4.0.]
 +
* 2024-01-18, 21:50:24: [https://github.com/kylebeggs/Numerical-Methods-in-Python kylebeggs/Numerical-Methods-in-Python: A collection of Python notebooks covering topics in an undergraduate Numerical Methods in Engineering course.]
 +
* 2024-01-18, 21:49:05: [https://github.com/sslotin/universum-dl sslotin/universum-dl: Some notebooks from a Deep Learning mini-course taught in Summer '18]
 +
* 2024-01-18, 21:43:06: [https://github.com/ali-tny/boyd-convex-optimisation-py ali-tny/boyd-convex-optimisation-py: homework notebooks for the Stanford Convex Optimisation course in python (rather than Matlab)]
 +
* 2024-01-18, 21:40:45: [https://github.com/Novota15/fourier-transforms-in-python Novota15/fourier-transforms-in-python: A jupyter python notebook that provides a crash course on Fourier Series, Fourier Transforms, Fast Fourier Transforms, and improving Chebyshev Interpolation with FFT]
 +
* 2024-01-18, 21:37:53: [https://github.com/nivkeren/computational-methods nivkeren/computational-methods: computational-methods course notebooks]
 +
* 2024-01-18, 21:36:24: [https://github.com/ptah23/audio-transformers-course-notebooks ptah23/audio-transformers-course-notebooks: Python notebooks for hugging face audio transformers course]
 +
* 2024-01-18, 21:31:16: [https://github.com/iutzeler/refresher-course iutzeler/refresher-course: Jupyter Notebooks for practical sessions of the "Refresher Course in Matrix Analysis and Numerical Optimization" at Université Grenoble Alpes]
 +
* 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, 19:50:04: [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, 19:49:32: [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.]

Версия 19:14, 20 марта 2024

2024

2024-03

2024-02

2024-01

2023

2023-11

2023-10

2023-09

2023-08

2023-06

2023-03

2022

2022-04

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

2022-03

2021

2021-12

2021-11

2021-10

2021-09

2021-08

2021-07

2021-06

2021-05

  • 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

2021-04

2021-03

2021-02

2021-01

2020

2020-12

2020-11

2020-10

2020-09

2020-08

2020-07

Источник — «https://discopal.ispras.ru/index.php?title=Участник:StasFomin/Bookmarks/Algorithms&oldid=28703»