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Transformer Decoder coded from scratch
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Transformers from scratch - Transformer Decoder coded from scratch

5.0 (4)
32 learners

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This course includes

  • 4.3 hours of video
  • Certificate of completion
  • Access on mobile and TV

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ABOUT ME β­• Subscribe: https://www.youtube.com/c/CodeEmporium?sub_confirmation=1 πŸ“š Medium Blog: https://medium.com/@dataemporium πŸ’» Github: https://github.com/ajhalthor πŸ‘” LinkedIn: https://www.linkedin.com/in/ajay-halthor-477974bb/ RESOURCES [ 1 πŸ”Ž] Blowing up the decoder archtecture: https://youtu.be/ekg-hoob0SM [ 2 πŸ”Ž] Code for video: https://github.com/ajhalthor/Transformer-Neural-Network/blob/main/Transformer_Decoder_EXPLAINED!.ipynb PLAYLISTS FROM MY CHANNEL β­• Transformers from scratch playlist: https://www.youtube.com/watch?v=QCJQG4DuHT0&list=PLTl9hO2Oobd97qfWC40gOSU8C0iu0m2l4 β­• ChatGPT Playlist of all other videos: https://youtube.com/playlist?list=PLTl9hO2Oobd9coYT6XsTraTBo4pL1j4HJ β­• Transformer Neural Networks: https://youtube.com/playlist?list=PLTl9hO2Oobd_bzXUpzKMKA3liq2kj6LfE β­• Convolutional Neural Networks: https://youtube.com/playlist?list=PLTl9hO2Oobd9U0XHz62Lw6EgIMkQpfz74 β­• The Math You Should Know : https://youtube.com/playlist?list=PLTl9hO2Oobd-_5sGLnbgE8Poer1Xjzz4h β­• Probability Theory for Machine Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd9bPcq0fj91Jgk_-h1H_W3V β­• Coding Machine Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd82vcsOnvCNzxrZOlrz3RiD MATH COURSES (7 day free trial) πŸ“• Mathematics for Machine Learning: https://imp.i384100.net/MathML πŸ“• Calculus: https://imp.i384100.net/Calculus πŸ“• Statistics for Data Science: https://imp.i384100.net/AdvancedStatistics πŸ“• Bayesian Statistics: https://imp.i384100.net/BayesianStatistics πŸ“• Linear Algebra: https://imp.i384100.net/LinearAlgebra πŸ“• Probability: https://imp.i384100.net/Probability OTHER RELATED COURSES (7 day free trial) πŸ“• ⭐ Deep Learning Specialization: https://imp.i384100.net/Deep-Learning πŸ“• Python for Everybody: https://imp.i384100.net/python πŸ“• MLOps Course: https://imp.i384100.net/MLOps πŸ“• Natural Language Processing (NLP): https://imp.i384100.net/NLP πŸ“• Machine Learning in Production: https://imp.i384100.net/MLProduction πŸ“• Data Science Specialization: https://imp.i384100.net/DataScience πŸ“• Tensorflow: https://imp.i384100.net/Tensorflow TIMESTAMP 0:00 Introduction 1:34 Parameters of Transformer 5:04 Inputs and Outputs of Transformer 6:11 Masking 7:16 Instantiating Decoder 9:07 Decoder Forward Pass 11:28 Decoder Layer 13:00 Masked Multi Head Self Attention 23:00 Dropout + Layer Normalization 28:09 Multi Head Cross Attention 34:34 Feed Forward, Activation 36:44 Completing the decoder flow

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