Это подкаст о машинном обучении от неспециалиста для неспециалистов. Буду рассказывать о развитии индустрии, проводить ликбез, объяснять терминологию и профессиональные жаргонизмы, общаться с профессионалами из индустрии Искусственного Интеллекта. Я сам не так давно начал погружаться в эту тему и по мере своего развития буду делиться своим пониманием этой интересной и перспективной области знаний. Почта для обратной связи: kms101@yandex.ru Сообщество подкаста в ВК: https://vk.com/mlpodcast Телеграм-канал: https://t.me/toBeAnMLspecialist Я в телеграме: @kmsint
Do you want to know how many people listen to Machine Learning Podcast? Or perhaps how many downloads it gets? Rephonic has scanned the web and collated all the information we found in our podcast database.
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В гостях Руслан Гончаров - современный дизайнер, автор телеграм-канала "Нейронная академия", автор многочисленных подробных гайдов по генерации изображений с помощью нейросетей. Обсудили с Русланом хайповую тему генерации изображений по текстовому оп... more
Общаемся с Данилой Медведевым - трансгуманистом и прикладным футурологом - о рисках, которые несет человечеству сильный искусственный интеллект и что с этим делать. Кто страшнее: злобный футуролог или василиск Роко? Кто такой Василий Сёрль? Как не по... more
В гостях выпуска Андрей Данильченко - специалист, отвечающий за качество геопоиска в Яндекс Картах. Андрей в Яндексе с 2011 года и успел прикоснуться к большому количеству сервисов своей экспертизой. Стоял у истоков Яндекс.Радио и Яндекс.Дзен, занима... more
Чирикают в никуда 😂
30 сознательных лет?) more
Виктория намного лучше Анастасии, приятнее гораздо слушать. И смеется смешно)
Юмор конечно на высоте - уснули и забыли выключить плеер это про кармика каолу😂
Захотелось посмотреть на ютубе твой объяснения, с картинками и стрелками)
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Machine Learning Podcast launched 4 years ago and published 50 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
Our systems regularly scour the web to find email addresses and social media links for this podcast. But in the unlikely event that you can't find what you're looking for, our concierge service lets you request our research team to source better contact information for you.
Our systems scan a variety of public sources including the podcast's official website, RSS feed, and email databases to provide you with a trustworthy source of podcast contact information. We also have our own research team on-hand to manually find email addresses if you can't find exactly what you're looking for.
Rephonic pulls reviews for Machine Learning Podcast from multiple sources, including Apple Podcasts, Castbox, Podcast Addict and more.
View all the reviews in one place instead of visiting each platform individually and use this information to decide whether this podcast is worth pitching as a guest or sponsor.
You can view podcasts similar to Machine Learning Podcast by exploring Rephonic's 3D interactive graph. This tool uses the data displayed on the 'Listeners Also Subscribed To' section of Apple Podcasts to visualise connections between shows.