http://v.michm.ru/index.php?action=history&feed=atom&title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C 2026-06-09T02:38:57Z История изменений этой страницы в вики MediaWiki 1.19.23 http://v.michm.ru/index.php?title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C&diff=39439&oldid=prev 2022-12-09T11:48:19Z

<p></p> <table class='diff diff-contentalign-left'> <col class='diff-marker' /> <col class='diff-content' /> <col class='diff-marker' /> <col class='diff-content' /> <tr valign='top'> <td colspan='2' style="background-color: white; color:black;">← Предыдущая</td> <td colspan='2' style="background-color: white; color:black;">Версия 11:48, 9 декабря 2022</td> </tr><tr><td colspan="2" class="diff-lineno">Строка 14:</td> <td colspan="2" class="diff-lineno">Строка 14:</td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background: #eee; color:black; font-size: smaller;"><div>8. Сравнение возможностей платформ для работы с Большими Данными</div></td><td class='diff-marker'>&#160;</td><td style="background: #eee; color:black; font-size: smaller;"><div>8. Сравнение возможностей платформ для работы с Большими Данными</div></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background: #eee; color:black; font-size: smaller;"><div>9. Архитектура и возможности облачной платформы Nubes</div></td><td class='diff-marker'>&#160;</td><td style="background: #eee; color:black; font-size: smaller;"><div>9. Архитектура и возможности облачной платформы Nubes</div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">10. Фильтрация экспериментальных данных. Алгоритм плавающего среднего, экспоненциальный фильтр. Рекуррентные алгоритмы. Оценка качества фильтрации. Выбор между качеством фильтрации и скоростью.&lt;br&gt;</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">12. Регрессионный анализ, основные допущения. Проверка значимости параметров и адекватности уравнения.&lt;br&gt;</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">13. Проверка адекватности математической модели.&lt;br&gt;</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">14. Структурная идентификация модели. Метод группового учёта аргументов. &lt;br&gt;</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">15. Определение параметров линейного уравнения регрессии методом наименьших квадратов.</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">16. Определение параметров линейного уравнения регрессии (простой и множественной) с использованием статистических характеристик.</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">17. Понятие о законах распределения &quot;Хи-квадрат&quot;, Стьюдента и Фишера. Примеры их использования. Понятие о статистических гипотезах и методах их проверки. Р- значение.</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">18. Определение параметров линейного уравнения регрессии в матричной форме.</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">19. Понятие о полном факторном эксперименте (ПФЭ). Построение планов ПФЭ, его свойства. Достоинства и недостатки. Определение параметров модели по данным полного факторного эксперимента, проверка их значимости, проверка адекватности модели.</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">20. Таблица дисперсионного анализа. Определение наличия регрессионной зависимости с использованием F - отношения. Множественный коэффициент корреляции.</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">21. Понятие о частном коэффициенте корреляции. Определение его значимости. Пример использования.</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">22. Методы последовательного уточнения структуры регрессионного уравнения: метод включений, метод исключений, метод пошаговой регрессии.</ins></div></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'>&#160;</td><td style="background: #eee; color:black; font-size: smaller;"></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'>&#160;</td><td style="background: #eee; color:black; font-size: smaller;"></td></tr> </table>

Dz http://v.michm.ru/index.php?title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C&diff=39438&oldid=prev 2022-12-09T11:46:20Z

<p></p> <table class='diff diff-contentalign-left'> <col class='diff-marker' /> <col class='diff-content' /> <col class='diff-marker' /> <col class='diff-content' /> <tr valign='top'> <td colspan='2' style="background-color: white; color:black;">← Предыдущая</td> <td colspan='2' style="background-color: white; color:black;">Версия 11:46, 9 декабря 2022</td> </tr><tr><td colspan="2" class="diff-lineno">Строка 1:</td> <td colspan="2" class="diff-lineno">Строка 1:</td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">Список вопросов:</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">1. Понятия и области применения Big Data (Большие Данные),&#160; Machine Learning (Машинное обучение), Artificial Intelligence (Искуственный Интеллект, ИИ), Deep Learning (глубокое обучение), Data Mining,&#160; Text Mining. Место Больших Данных в современных информационных и интеллектуальных системах.</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">2. Основные характеристики Больших Данных - разнообразие, высокая скорость поступления и большой объем. Требования к системам обработки БД -&#160; надёжность и отказоустойчивость (как от аппаратных проблем, так и от человеческого фактора); малые задержки чтения и записи данных; масштабируемость; обобщение; расширяемость; поддержка произвольного доступа; минимальное сопровождение; отлаживаемость. Недостатки инкрементных архитектур. Лямбда-архитектура. </ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">3. Системы параллельной обработки (MapReduce).&#160; Эластичные облака (IaaS). Системы пакетных вычислений (Hadoop – HDFS + MapReduce). Каркасы сериализации (Apachy Thrift).&#160; NoSQL (MongoDB, Cassandra). Системы обмена сообщениями и диспетчера очередей (Apachy Kafka). Системы вычислений в реальном времени (Apachy Storm).</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">4. Существующие на рынке сервисы и платформы: Yandex DataSphere, Microsoft Azure, AWS. Интеграция Big Data и&#160; Machine Learning.</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">5. Архитектура и возможности сервиса Yandex DataSphere</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">6. Архитектура и возможности облачной платформы Microsoft Azure</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">7. Архитектура и возможности облачной платформы AWS</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">8. Сравнение возможностей платформ для работы с Большими Данными</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;">9. Архитектура и возможности облачной платформы Nubes</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background: #eee; color:black; font-size: smaller;"><div>09.09.2022 Лекция 1. 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Dz http://v.michm.ru/index.php?title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C&diff=38875&oldid=prev 2022-10-07T11:13:27Z

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Dz http://v.michm.ru/index.php?title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C&diff=38874&oldid=prev 2022-10-07T11:12:06Z

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Dz http://v.michm.ru/index.php?title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C&diff=38471&oldid=prev 2022-09-16T10:36:17Z

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Пичугин Михаил http://v.michm.ru/index.php?title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C&diff=38470&oldid=prev 2022-09-16T10:21:23Z

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Dz http://v.michm.ru/index.php?title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C&diff=38312&oldid=prev 2022-09-10T09:02:13Z

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Ноль Эльвира http://v.michm.ru/index.php?title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C&diff=38305&oldid=prev 2022-09-09T12:32:50Z

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Оралов Иван http://v.michm.ru/index.php?title=%D0%91%D0%BE%D0%BB%D1%8C%D1%88%D0%B8%D0%B5_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D0%B5_2022_%D0%BE%D1%81%D0%B5%D0%BD%D1%8C&diff=38304&oldid=prev 2022-09-09T12:27:06Z

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Чернова Ольга