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Contenu fourni par Emily Laird. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Emily Laird ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
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Deep Learning Mini Series: What are Recurrent Neural Networks (RNNs)?
Manage episode 424766417 series 3578824
Contenu fourni par Emily Laird. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Emily Laird ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
In this episode of our deep learning mini-series, we explore Recurrent Neural Networks (RNNs). Imagine reading a mystery novel, keeping track of all the clues and characters—RNNs are like your super-intelligent reading buddy, remembering past events to make sense of the present. Perfect for processing sequences of data like text and speech, RNNs are valuable where context matters. We’ll explore their key components, such as recurrent layers and hidden states, and see real-world applications from language translation to financial forecasting.
Connect with Emily Laird on LinkedIn
72 episodes
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Manage episode 424766417 series 3578824
Contenu fourni par Emily Laird. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Emily Laird ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
In this episode of our deep learning mini-series, we explore Recurrent Neural Networks (RNNs). Imagine reading a mystery novel, keeping track of all the clues and characters—RNNs are like your super-intelligent reading buddy, remembering past events to make sense of the present. Perfect for processing sequences of data like text and speech, RNNs are valuable where context matters. We’ll explore their key components, such as recurrent layers and hidden states, and see real-world applications from language translation to financial forecasting.
Connect with Emily Laird on LinkedIn
72 episodes
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Lecteur FM recherche sur Internet des podcasts de haute qualité que vous pourrez apprécier dès maintenant. C'est la meilleure application de podcast et fonctionne sur Android, iPhone et le Web. Inscrivez-vous pour synchroniser les abonnements sur tous les appareils.
Similaire à Generative AI 101
Africa-focused technology, digital and innovation ecosystem insight and commentary.
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continue reading
Show notes are at https://stevelitchfield.com/sshow/chat.html
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A podcast featuring panelists of engineers from Netflix, Twitch, & Atlassian talking over drinks about all things software engineering.
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continue reading
Three nerds discussing tech, Apple, programming, and loosely related matters.
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continue reading
Download This Show is your weekly guide to the world of media, culture, and technology. From social media to gadgets, streaming services to privacy issues. Each week Marc Fennell and a team of people far smarter than him (his words, not ours) take a fun deep dive into how technology is reshaping our lives.
…
continue reading
This is the audio podcast version of Troy Hunt's weekly update video published here: https://www.troyhunt.com/tag/weekly-update/
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continue reading
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…
continue reading
Every Friday and Sunday, Slate’s popular daily news podcast What Next brings you TBD, a clear-eyed look into the future. From fake news to fake meat, algorithms to augmented reality, Lizzie O’Leary is your guide to the tech industry and the world it’s creating for us to live in.
…
continue reading
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…
continue reading
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