Encoder Decoder | Sequence-to-Sequence Architecture | Deep Learning | CampusX

In this video, we unravel the complexities of the Encoder-Decoder architecture, focusing on its application in sequence-to-sequence tasks. Whether you're a student, developer, or tech enthusiast, join us on this learning journey as we break down the fundamentals of this powerful model. Digital Notes for Deep Learning: https://shorturl.at/NGtXg 🔗 Research Paper: https://arxiv.org/pdf/1409.3215.pdf ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science! Share your thoughts, experiences, or questions in the comments below. I love hearing from you! Thank you for joining us on this exploration of the Encoder-Decoder architecture. Stay curious, and let's decode the future together! 🚀🤖 ⌚Time Stamps⌚ 00:00 - Intro 01:22 - SEQ2SEQ Data 08:04 - Things to Know Before You Start 10:05 - High Level Overview 13:43 - What's under the hood? 19:25 - Training the Architecture using Backpropagation 48:44 - Prediction 55:35 - Improvement 1 - Embeddings 1:00:30 - Improvement 2 - Deep LSTMs 1:10:45 - Original Research Paper 1:10:58 - The Sutskever Architecture ✨ Hashtags✨ #EncoderDecoder #SequenceToSequence #DeepLearning #MachineLearning #CampusX #TechExplained #AI #NeuralNetworks #LSTM #AlgorithmExplained