by FaangTalk.org
Email Addresses
1 available
Phone Numbers
0 available
October 8, 2024
<p><a href="https://www.youtube.com/live/ZY6NbHMYdLk">#FaangTalk 70 - Personalized News Feed | Разбор кейса ML System Design Interview</a></p> <p>Обсуждаем главу 10 Personalized News Feed из книги ML System Design Interview от Алекса Ксю. В гостях Павел Елизаров</p> <p>Chapters</p> <p>00:00 Введение в ML System Design Interview</p> <p>02:50 Этапы интервью и условия задачи</p> <p>06:05 Определение метрик и целей системы</p> <p>08:57 Сигналы пользователей и их влияние на персонализацию</p> <p>12:09 Явные и неявные сигналы пользователей</p> <p>15:52 Метрики вовлеченности и их значение</p> <p>19:34 Серендипити: Счастливые случайности в контенте</p> <p>23:22 Явные и неявные сигналы в контенте</p> <p>30:16 Фичи и их роль в рекомендательных системах</p> <p>31:44 Построение рекомендательных систем</p> <p>38:12 Фичи постов и их анализ</p> <p>43:01 Фичи пользователей и их влияние</p> <p>46:43 Моделирование и оценка результатов</p> <p>47:12 Оптимизация нейронных сетей и многозадачность</p> <p>49:43 Методы обучения и адаптации моделей</p> <p>51:48 Функции потерь и их применение</p> <p>54:04 Оценка моделей и метрики</p> <p>56:39 Оптимизация вычислительных ресурсов</p> <p>59:18 Сервинг моделей и этапы обработки данных</p> <p>01:01:35 Модели и новые типы контента</p> <p>01:04:28 A/B тестирование и его значение</p> <p>01:15:34 Персонализированные рекомендательные системы</p> <iframe width="560" height="315" src="https://www.youtube.com/embed/ZY6NbHMYdLk?si=i8R_jPn4qBkep3Vy" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at [email protected] for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.