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PLAYLISTS FROM MY CHANNEL
⭕ Reinforcement Learning:    • Reinforcement Learning 101  
Natural Language Processing:    • Natural Language Processing 101  
⭕ Transformers from Scratch:    • Natural Language Processing 101  
⭕ ChatGPT Playlist:    • ChatGPT  
⭕ Convolutional Neural Networks:    • Convolution Neural Networks  
⭕ The Math You Should Know :    • The Math You Should Know  
⭕ Probability Theory for Machine Learning:    • Probability Theory for Machine Learning  
⭕ Coding Machine Learning:    • Code Machine Learning  


MATH COURSES (7 day free trial)
Mathematics for Machine Learning: https://imp.i384100.net/MathML
Calculus: https://imp.i384100.net/Calculus
Statistics for Data Science: https://imp.i384100.net/AdvancedStati...
Bayesian Statistics: https://imp.i384100.net/BayesianStati...
Linear Algebra: https://imp.i384100.net/LinearAlgebra
Probability: https://imp.i384100.net/Probability

OTHER RELATED COURSES (7 day free trial)
⭐ Deep Learning Specialization: https://imp.i384100.net/DeepLearning
Python for Everybody: https://imp.i384100.net/python
MLOps Course: https://imp.i384100.net/MLOps
Natural Language Processing (NLP): https://imp.i384100.net/NLP
Machine Learning in Production: https://imp.i384100.net/MLProduction
Data Science Specialization: https://imp.i384100.net/DataScience
Tensorflow: https://imp.i384100.net/Tensorflow

REFERENCES
[1] The main Paper: https://arxiv.org/abs/1706.03762
[2] Tensor2Tensor has some code with a tutorial: https://www.tensorflow.org/tutorials/...
[3] Transformer very intuitively explained Amazing: http://jalammar.github.io/illustrated...
[4] Medium Blog on intuitive explanation:   / whatisatransformer  
[5] Pretrained word embeddings: https://nlp.stanford.edu/projects/glove/
[6] Intuitive explanation of Layer normalization: https://mlexplained.com/2018/11/30/an...
[7] Paper that gives even better results than transformers (Pervasive Attention): https://arxiv.org/abs/1808.03867
[8] BERT uses transformers to pretrain neural nets for common NLP tasks. : https://ai.googleblog.com/2018/11/ope...
[9] Stanford Lecture on RNN: http://cs231n.stanford.edu/slides/201...
[10] Colah’s Blog: https://colah.github.io/posts/201508...
[11] Wiki for timeseries of events: https://en.wikipedia.org/wiki/Transfo...)