- ML Models represented as Data Structure or Program
- Data Structure - Graph (Deferred Execution - Define and Run)
- Model - Program - Python Code (Eager Execution - Define by Run)
- Tensorflow is both Data Structure and Model
- Has both CPU and GPU Support
- Model is Data Structure - Easy to Serialize and De-Serialize it and Deploy on Devices (Mobile, TPU, XLA)
- Because model is data structure it is not tied down to language
- Distributed Training to train on large amount of data
- Model Structures - Convolution, AvgPool, MaxPool, Concat, Dropout, FullyConnected, Softmax
- Traditional RNN vs Dynamic Models
- Model whose structure cannot be easily defined by graph
- Straightforward with Eager using Native Python control flow
Happy Mastering DL!!!
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