RNN Introduction Generative Ai Basic to Advance

>> YOUR LINK HERE: ___ http://youtube.com/watch?v=S1IMX8A-Ksk

Sign up with Euron today : https://euron.one/sign-up?ref=430A5AD3 • Unlock your potential with Learning Logic and dive deep into the world of Recurrent Neural Networks (RNNs) with Prince Katiyar! In this video, we explore the 5 crucial RNN concepts you must master today to transform your career and elevate your tech skills. Discover the truth behind RNN architectures, their need, backpropagation, and how they excel in handling sequential data. From time series analysis to NLP and image captioning, we'll explore real-world use cases. Explore now and don't miss out on the opportunity to understand how RNNs solve challenges like unequal data lengths and parameter sharing. Are you ready to transform your projects? Watch now, and if you believe in these insights, share this video to reach as many people as possible. Subscribe to Learning Logic, hit the bell icon for the latest tech updates, and join us on this exciting educational journey! #AI #ArtificialIntelligence #coding #techjobs #programming #CareerJourneyTips • Material Link : https://euron.one/course/generative-a... • CHAPTERS: • 00:00 - Intro • 00:28 - Importance of Recurrent Neural Networks • 01:00 - What is RNN • 01:24 - Need for RNN • 01:41 - RNN Architecture • 02:07 - Applications of RNN • 02:45 - How RNN Works • 03:16 - Key Takeaways • 03:45 - Basic Architecture of Late Spots • 04:32 - Late Spots Architecture - Example 1 • 05:49 - Late Spots Architecture - Example 2 • 09:02 - Understanding RNN Challenges • 09:05 - What is Padding • 09:35 - Padding - Avoiding Excess Spaces • 09:52 - Padding - Defining Space • 10:25 - How to Use Predictions • 10:38 - Understanding Images in RNN • 11:51 - Diagram Creation Process • 12:41 - Pass Method Explained • 15:52 - Model Architecture Overview • 16:16 - Solving Unequal Length Issues • 17:45 - Understanding the Arrow Concept • 17:55 - What is Goel Goel Rekent • 18:05 - Time Period System Sort Explained • 18:15 - Key Learnings • 18:25 - Important Concepts to Learn • 18:35 - Model Learning Essentials • 18:45 - Sharing Essential Knowledge • 21:14 - First Formula Creation • 22:38 - Last Formula Creation • 25:17 - Parameter Calculation Process • 25:42 - Notes Count in Last Layer • 26:37 - Calculating Layer Parameters • 27:10 - Forward Pass in Neural Networks • 27:40 - Session Wrap-Up • • Instagram: https://www.instagram.com/euron_offic... • YouTube: / @euron-official • WhatsApp :https://whatsapp.com/channel/0029Vaee... • LinkedIn: https://www.linkedin.com/company/euro... • Facebook: / 61566117690191 • Twitter :https://x.com/i/flow/login?redirect_a...

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