#IntuitiveDeepLearning #SimpleMathematicsOfDL #LinearAlgebra
Unlock the world of Deep Learning with our new “Intuitive Deep Learning” video series!
🚀 Dive into the mathematical foundations of DL using an intuitive approach and the power of linear algebra.
🧠 We hope that you will find the joy of clarity and multi-layer understanding of DL methods in this new series.
In this video we briefly cover the following topics:
1. K-mearns using matrix factorization
2. Sparse coding using matrix factorization
3. Generalized matrix factorization
📚🔗 The summary map of the DL linear algebra of the first lecture videos 1.1 to 1.6 can be found at: https://drive.google.com/file/d/198s8Tr8AGHplQaRZXcLawshiakGTxXKA/view?usp=sharing
📚🔗 Access the lecture material here: https://drive.google.com/file/d/1PDdH_pa9jbpKd3LpzPy_KuOKHSV0tygY/view?usp=sharing
📊💡 Join us on this journey to gain a simplified understanding of complex concepts in DL.
Special thanks go to Jeremey Watts, Simon Prince and co-authors for producing foundational textbooks:
• Machine Learning Refined; https://github.com/jermwatt/machine_learning_refined
• Understanding Deep Learning; https://github.com/udlbook/
