Lec5
Training Neural Networks II: Weight Initialization(Activation Statistics, Xavier Initialization, Kaiming / MSRA Initialization, Residual Networks…), Overfits, Regularization, Regularization, Data Augmentation
Training networks
Lec2
Introduction of Neural Networks I,Deep Neural Networks, Activation Fuctions
Neural networks
Lec3
Introduction of Neural Networks II,Universal Approximation, Convex Fuctions.
2 Video & PDF
https://www.distributed-systems.net/index.php/books/ds3/
This course provides a comprehensive introduction to the principles and practices of distributed systems. Topics include concurrency, fault tolerance, and consistency.
Distributed SystemsConcurrencyFault ToleranceConsistency
This module covers fundamental concepts like what constitutes a distributed system, different architectures, and challenges in designing them.
1
Distributed SystemsArchitectureDesign
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