Участник:StasFomin/Bookmarks/Algorithms — различия между версиями

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(Добавлена закладка rogerorr/NtTrace: An strace-like program for the Windows 'native' API)
(Добавлена закладка Add support for live share · Issue #388 · coder/code-server · GitHub)
 
(не показано 89 промежуточных версий этого же участника)
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== 2024 ==
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=== 2024-05 ===
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* 2024-05-31, 00:40:21: [https://github.com/coder/code-server/issues/388 Add support for live share · Issue #388 · coder/code-server · GitHub]
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*: <html>Just want to say that I am currently able to download and install the .vsix, and Live Share (1.0.5857) works for me on code-server (4.11.0).</html>
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* 2024-05-21, 21:45:24: [https://habr.com/ru/companies/alfa/articles/748824/ Единая нейросетевая модель кредитного скоринга / Хабр]
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=== 2024-04 ===
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* 2024-04-18, 03:27:43: [https://arxiv.org/abs/2104.00480 (2104.00480) Idris 2: Quantitative Type Theory in Practice]
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=== 2024-03 ===
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* 2024-03-28, 16:34:00: [https://docs.google.com/spreadsheets/d/1ioHOHnPrcj6qBrsxotYVeVJVlkqHj2GD/edit?pli=1#gid=1316239506 статус курсы.xlsx - Google Sheets]
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* 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)]
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* 2024-03-03, 19:22:07: [https://sysblok.ru/knowhow/kak-ustroena-nejroset-bert-ot-google/ Как устроена нейросеть BERT от Google - Системный Блокъ]
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* 2024-03-03, 19:13:07: [https://github.com/LeorFinkelberg/Optimization LeorFinkelberg/Optimization]
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=== 2024-02 ===
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* 2024-02-27, 20:55:59: [https://vk.com/video-176869000_456239030 Video005 — Видео]
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=== 2024-01 ===
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* 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]
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* 2024-01-27, 07:05:06: [https://habr.com/ru/companies/glowbyte/articles/519382/ ML и DS оттенки кредитного риск-менеджмента / Хабр]
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* 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]
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* 2024-01-26, 03:06:01: [https://habr.com/ru/companies/yandex/articles/263991/ Вероятностное программирование / Хабр]
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* 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]
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* 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]
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* 2024-01-20, 00:29:21: [https://github.com/tlkahn/zkSNARKs-Cryptography-Protocol-Survey tlkahn/zkSNARKs-Cryptography-Protocol-Survey]
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* 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]
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* 2024-01-19, 23:12:56: [https://zhuanlan.zhihu.com/p/37270132 Теорема PCP, часть 1: Введение - Чжиху]
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* 2024-01-19, 23:07:56: [https://github.com/mourad1081/complexity-exam-questions mourad1081/complexity-exam-questions: Réponse aux questions de complexité]
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* 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]
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* 2024-01-19, 22:51:02: [https://github.com/BrownAppliedCryptography/notes BrownAppliedCryptography/notes: Scribed course notes.]
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* 2024-01-19, 22:49:27: [https://github.com/mnielsen/expander_graph_notes mnielsen/expander_graph_notes: Notes on expander graphs]
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* 2024-01-19, 22:48:32: [https://github.com/pragmaticTNT pragmaticTNT]
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* 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]
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* 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]
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* 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]
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* 2024-01-19, 01:41:18: [https://github.com/arielgabizon/Lectures/blob/master/4elemproofAarhus2019.pdf Lectures/4elemproofAarhus2019.pdf at master · arielgabizon/Lectures]
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* 2024-01-19, 01:10:29: [https://github.com/Landarzar/complexityPoster/blob/master/poster.pdf complexityPoster/poster.pdf at master · Landarzar/complexityPoster]
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* 2024-01-19, 00:54:25: [https://github.com/jarrodmillman/pcp/blob/master/final.tex pcp/final.tex at master · jarrodmillman/pcp]
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* 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.]
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* 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!]
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* 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)]
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* 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.]
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* 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.]
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* 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]
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* 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)]
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* 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]
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* 2024-01-18, 21:37:53: [https://github.com/nivkeren/computational-methods nivkeren/computational-methods: computational-methods course notebooks]
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* 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]
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* 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]
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* 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.]
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* 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.]
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* 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]
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* 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]
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* 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)]
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* 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]
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* 2024-01-18, 21:13:14: [https://github.com/Unipisa/HLT Unipisa/HLT: Notebooks for course HLT]
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* 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.]
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* 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]
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* 2024-01-18, 21:09:14: [https://github.com/iutzeler/NumericalOptimization/tree/master/Lab2_GradientDescent NumericalOptimization/Lab2_GradientDescent at master · iutzeler/NumericalOptimization]
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* 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]
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* 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]
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* 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]
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* 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"]
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* 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)]
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* 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.]
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* 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]
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* 2024-01-18, 19:47:48: [https://github.com/yourwanghao/CMUComputationalPhotography yourwanghao/CMUComputationalPhotography: Jupyter Notebooks for CMU Computational Photography Course 15.463]
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* 2024-01-18, 19:45:02: [https://github.com/lmarti/evolutionary-computation-course lmarti/evolutionary-computation-course: Jupyter/IPython notebooks about evolutionary computation.]
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* 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]
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* 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]
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* 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]
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* 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)]
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* 2024-01-16, 07:43:04: [https://github.com/xuwenhao/geektime-ai-course xuwenhao/geektime-ai-course: Jupyter Notebooks for Geektime AI Course]
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* 2024-01-16, 07:42:49: [https://github.com/ML-course/master ML-course/master: A machine learning course using Python, Jupyter Notebooks, and OpenML]
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* 2024-01-16, 07:39:44: [https://github.com/dataflowr/notebooks dataflowr/notebooks: code for deep learning courses]
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* 2024-01-16, 07:38:51: [https://github.com/FurkanGozukara/Stable-Diffusion FurkanGozukara/Stable-Diffusion: Stable Diffusion, SDXL, LoRA Training, DreamBooth Training, Automatic1111 Web UI, DeepFake, Deep Fakes, TTS, Animation, Text To Video, Tutorials, Guides, Lectures, Courses, ComfyUI, Google Colab, RunPod, NoteBooks, ControlNet, TTS, Voice Cloning, AI, AI News, ML, ML News, News, Tech, Tech News, Kohya LoRA, Kandinsky 2, DeepFloyd IF, Midjourney]
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* 2024-01-16, 07:37:44: [https://github.com/phlippe/uvadlc_notebooks phlippe/uvadlc_notebooks: Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022]
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* 2024-01-16, 07:36:44: [https://github.com/fastai/course22 fastai/course22: The fast.ai course notebooks]
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* 2024-01-16, 07:35:36: [https://github.com/mlabonne/llm-course mlabonne/llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.]
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* 2024-01-16, 07:30:12: [https://github.com/peremartra/Large-Language-Model-Notebooks-Course peremartra/Large-Language-Model-Notebooks-Course: Practical course about Large Language Models.]
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* 2024-01-16, 07:29:16: [https://github.com/aperham90/QS_combinatorics/blob/main/Oralists_Aug142023.ipynb QS_combinatorics/Oralists_Aug142023.ipynb at main · aperham90/QS_combinatorics]
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* 2024-01-16, 07:28:41: [https://github.com/fastai/numerical-linear-algebra/blob/master/nbs/2.%20Topic%20Modeling%20with%20NMF%20and%20SVD.ipynb numerical-linear-algebra/nbs/2. Topic Modeling with NMF and SVD.ipynb at master · fastai/numerical-linear-algebra]
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== 2023 ==
 
== 2023 ==
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=== 2023-11 ===
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* 2023-11-12, 16:18:02: [https://github.com/d-kirsanov/fresheye/blob/master/Code.gs fresheye/Code.gs at master · d-kirsanov/fresheye]
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* 2023-11-11, 17:52:20: [https://github.com/bitbank2/TIFF_G4 bitbank2/TIFF_G4: A set of highly optimized functions for decoding and displaying 1-bpp CCITT G4 images]
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=== 2023-10 ===
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* 2023-10-19, 07:40:49: [https://www.researchgate.net/publication/267146475_Lectures_on_Sphere_Arrangements_-_the_Discrete_Geometric_Side (3) Lectures on Sphere Arrangements – the Discrete Geometric Side | Request PDF]
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* 2023-10-02, 23:59:09: [https://sproul.xyz/blog/posts/gurobi-academic-validation.html How to Partially Bypass Gurobi's Academic IP Validation - sproul.xyz]
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=== 2023-09 ===
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* 2023-09-17, 22:31:02: [https://www.hindawi.com/journals/scn/2020/4195852/ Efficient Privacy-Preserving Fingerprint-Based Authentication System Using Fully Homomorphic Encryption]
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* 2023-09-17, 22:30:48: [https://github.com/taeyun1010/HomFingerPrintAuth taeyun1010/HomFingerPrintAuth]
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=== 2023-08 ===
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* 2023-08-05, 16:03:43: [https://www.math.auckland.ac.nz/~sgal018/crypto-book/ch17.pdf ch17.pdf]
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* 2023-08-05, 16:03:30: [https://github.com/kelbyludwig?tab=followers kelbyludwig (Kelby Ludwig) / Followers]
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=== 2023-06 ===
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* 2023-06-06, 16:10:06: [https://github.com/Geometrein/dashmap.io Geometrein/dashmap.io: DashMap is an open source web platform that gathers, analyses and visualises urban data.]
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* 2023-06-06, 15:51:02: [https://github.com/nhabbash/transport-network-analysis/tree/master nhabbash/transport-network-analysis: Graph-based analysis of a city's public transportation network]
 +
* 2023-06-05, 05:58:48: [https://github.com/search?q=pyrosm+plotly+language%3APython&type=code Code search results · GitHub]
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* 2023-06-05, 05:58:34: [https://wiki.openstreetmap.org/wiki/PBF_Format PBF Format — OpenStreetMap Wiki]
 +
* 2023-06-05, 05:56:56: [https://github.com/winstonyym/urbanity/tree/db0fa19f0ced219b1bbf4daf146474c649d0d765 GitHub - winstonyym/urbanity at db0fa19f0ced219b1bbf4daf146474c649d0d765]
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=== 2023-03 ===
 
=== 2023-03 ===
  
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* 2023-03-20, 11:52:55: [https://github.com/NVukobrat/CASIA-Iris-Recognition/tree/master/code CASIA-Iris-Recognition/code at master · NVukobrat/CASIA-Iris-Recognition]
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*: <html>          <span class="author flex-self-stretch" itemprop="author">      <a class="url fn" rel="author" data-hovercard-type="user" data-hovercard-url="/users/NVukobrat/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" href="https://github.com/NVukobrat">        NVukobrat </a>    </span>    <span class="mx-1 flex-self-stretch color-fg-muted">/</span>    <strong itemprop="name" class="mr-2 flex-self-stretch">      <a data-pjax="#repo-content-pjax-container" data-turbo-frame="repo-content-turbo-frame" href="https://github.com/NVukobrat/CASIA-Iris-Recognition">CASIA-Iris-Recognition</a></strong></html>
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* 2023-03-14, 22:56:49: [https://github.com/rogerorr/NtTrace rogerorr/NtTrace: An strace-like program for the Windows 'native' API]
 
* 2023-03-14, 22:56:49: [https://github.com/rogerorr/NtTrace rogerorr/NtTrace: An strace-like program for the Windows 'native' API]
 
* 2023-03-14, 22:52:46: [https://docs.pyvista.org/examples/00-load/create-point-cloud.html Create Point Cloud — PyVista 0.38.4 documentation]
 
* 2023-03-14, 22:52:46: [https://docs.pyvista.org/examples/00-load/create-point-cloud.html Create Point Cloud — PyVista 0.38.4 documentation]
Строка 14: Строка 137:
 
* 2023-03-08, 23:08:15: [https://en.wikipedia.org/wiki/Christofides_algorithm Christofides algorithm - Wikipedia]
 
* 2023-03-08, 23:08:15: [https://en.wikipedia.org/wiki/Christofides_algorithm Christofides algorithm - Wikipedia]
 
*: <html>In July 2020 however, Karlin, Klein, and Gharan released a preprint in which they introduced a novel approximation algorithm and claimed that its approximation ratio is 1.5&nbsp;−&nbsp;10<sup>−36</sup>. Their method follows similar principles to Christofides' algorithm, but uses a randomly chosen tree from a carefully chosen random distribution in place of the minimum spanning tree.<sup id="cite_ref-5" class="reference"><a href="https://en.wikipedia.org/wiki/#cite_note-5">[5]</a></sup><sup id="cite_ref-6" class="reference"><a href="https://en.wikipedia.org/wiki/#cite_note-6">[6]</a></sup> The paper was published at <a href="https://en.wikipedia.org/wiki/Symposium_on_Theory_of_Computing" title="Symposium on Theory of Computing">STOC'21</a><sup id="cite_ref-7" class="reference"><a href="https://en.wikipedia.org/wiki/#cite_note-7">[7]</a></sup> where it received a best paper award.<sup id="cite_ref-8" class="reference"><a href="https://en.wikipedia.org/wiki/#cite_note-8">[8]</a></sup></html>
 
*: <html>In July 2020 however, Karlin, Klein, and Gharan released a preprint in which they introduced a novel approximation algorithm and claimed that its approximation ratio is 1.5&nbsp;−&nbsp;10<sup>−36</sup>. Their method follows similar principles to Christofides' algorithm, but uses a randomly chosen tree from a carefully chosen random distribution in place of the minimum spanning tree.<sup id="cite_ref-5" class="reference"><a href="https://en.wikipedia.org/wiki/#cite_note-5">[5]</a></sup><sup id="cite_ref-6" class="reference"><a href="https://en.wikipedia.org/wiki/#cite_note-6">[6]</a></sup> The paper was published at <a href="https://en.wikipedia.org/wiki/Symposium_on_Theory_of_Computing" title="Symposium on Theory of Computing">STOC'21</a><sup id="cite_ref-7" class="reference"><a href="https://en.wikipedia.org/wiki/#cite_note-7">[7]</a></sup> where it received a best paper award.<sup id="cite_ref-8" class="reference"><a href="https://en.wikipedia.org/wiki/#cite_note-8">[8]</a></sup></html>
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* 2023-03-07, 20:02:36: [https://onlinelibrary.wiley.com/doi/epdf/10.1002/acp.3899?fbclid=IwAR3SmUXAPumu1S41bJV0KN5SkHxRgW7tX1apQhl79IVMX9MMJdxiYhRKrqw&af=R Learning in double time: The effect of lecture video speed on immediate and delayed comprehension]
 
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*: <html><span style="left: 76.063px; top: 118.043px; font-size: 15px; font-family: sans-serif; transform: scaleX(1.26741);" dir="ltr">RESEARCH ARTICLE</span><span style="left: 76.063px; top: 184.874px; font-size: 30px; font-family: sans-serif; transform: scaleX(0.881798);" dir="ltr">Learning in double time: The effect of lecture video speed on</span><span style="left: 76.063px; top: 223.142px; font-size: 30px; font-family: sans-serif; transform: scaleX(0.871663);" dir="ltr">immediate and delayed comprehension</span></html>
 
 
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* 2022-04-27, 22:04:58: [http://nicktitterton.com/SDPmaxcut.html Nick Titterton]
 
* 2022-04-27, 22:04:58: [http://nicktitterton.com/SDPmaxcut.html Nick Titterton]
 
*: <html>X = cvx.Variable((V, V), PSD=True) </html>
 
*: <html>X = cvx.Variable((V, V), PSD=True) </html>
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* 2022-04-27, 15:10:17: [https://www.gurobi.com/downloads/free-academic-license/ Academic License Detail - Gurobi]
 
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*: <html>grbgetkey fe05e206-c63b-11ec-acdf-0242c0a89004</html>
 
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=== 2022-03 ===
 
=== 2022-03 ===
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=== 2021-04 ===
 
=== 2021-04 ===
  
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* 2021-04-21, 16:49:25: [https://www.youtube.com/watch?v=j97K7VaIW5w Российское ПО - драйвер развития цифровой образовательной среды - YouTube]
 
 
* 2021-04-15, 06:40:47: [https://people.sc.fsu.edu/~jburkardt/datasets/knapsack_multiple/knapsack_multiple.html KNAPSACK_MULTIPLE - Data for the 01 Multiple Knapsack Problem]
 
* 2021-04-15, 06:40:47: [https://people.sc.fsu.edu/~jburkardt/datasets/knapsack_multiple/knapsack_multiple.html KNAPSACK_MULTIPLE - Data for the 01 Multiple Knapsack Problem]
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* 2021-04-11, 12:56:17: [https://www.iso.org/standard/69659.html ISO - ISO 6710:2017 - Single-use containers for human venous blood specimen collection]
 
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*: <html><h1>ISO 6710:2017</h1>  <h2 class="no-uppercase">Single-use containers for human venous blood specimen collection</h2></html>
 
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* 2021-04-11, 12:53:52: [http://www.transfusion.ru/2016/08-31-2.pdf 08-31-2.pdf]
 
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*: <html><span style="left: 200.833px; top: 913.089px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.929423);">Основным  видом  биологического  материала,  который  подвергаются  анализу  в </span><span style="left: 141.84px; top: 932.289px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.875458);">централизованной</span><span style="left: 298.633px; top: 932.289px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.899177);">КДЛ,  являются  кров.  Кровь  состоит  из  клеток  (эритроциты,  лейкоциты  и </span><span style="left: 141.84px; top: 951.289px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.882473);">тромбоциты)  и  жидкой  части,  которая  представляет  собой  раствор  многих  неорганических  и </span><span style="left: 141.84px; top: 970.489px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.872094);">органических веществ. Эта и есть та жидкость, которую анализируют в большинстве лабораторных </span><span style="left: 141.84px; top: 989.689px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.867393);">тестов</span><span style="left: 192.633px; top: 989.689px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.991228);">.  Поэтому  первым  этапом  после  взятия  проб  крови  и  перед  отправкой </span><span style="left: 877.967px; top: 989.689px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.845667);">их</span><span style="left: 912.6px; top: 989.689px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.916904);">в </span><span style="left: 141.84px; top: 1008.89px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.873458);">централизованную</span><span style="left: 309.883px; top: 1008.89px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.946979);">КДЛ,  является  отделение  жидкой  части  крови  от  клеток  путем </span><span style="left: 141.84px; top: 1028.09px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.884663);">центрифугирования  проб.  Жидкая  часть  крови,  которую  получают  после  центрифугирования, </span><span style="left: 141.84px; top: 1047.29px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.893618);">может быть плазмой  или сывороткой. </span><span style="left: 454.883px; top: 1047.29px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.886579);">Различие между  плазмой  и сывороткой</span><span style="left: 781.767px; top: 1047.29px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.882682);">должна понимать </span><span style="left: 141.84px; top: 1066.29px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.870898);">медицинская сестра при </span><span style="left: 337.083px; top: 1066.29px; font-size: 16.6px; font-family: sans-serif; transform: scaleX(0.870011);">взятии проб крови.</span></html>
 
 
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* 2021-04-09, 06:30:07: [https://interview.cups.online/live-coding/?room=97803a89-5a70-4eee-9017-a2ebfd6dbc8b Code Editor]
 
* 2021-04-09, 06:30:07: [https://interview.cups.online/live-coding/?room=97803a89-5a70-4eee-9017-a2ebfd6dbc8b Code Editor]

Текущая версия на 00:40, 31 мая 2024

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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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