GitHub - k-karna/tensorflow2_dl: Tensorflow 2: for Deep Learning Specialization

Module 1: Getting Started with Tensorflow 2 -- Sequential API, validation,regularization, callbacks, early stoppinga and patience, saving and loading model weights, saving and loading architecture, and loading pre-trained models
Module 2: Customization Your Models with Tensorflow 2 -- Functional API, Data Pipeline, Sequence Modelling - RNNs, Stacked, Bidirectional, stateful, model subclassing, and custom training loops
Module 3: Probabilistic Deep Learning with Tensorflow 2 -- Probabilistic layers, Bayesian Neural Networks, Bayesian CNN, Bijectors and normalising flows, Variational AutoEncoder, KL Divergence

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
Probabilistic_Deep_Learning		Probabilistic_Deep_Learning
Mod1_Capstone Project.ipynb		Mod1_Capstone Project.ipynb
Mod1_Capstone Project.pdf		Mod1_Capstone Project.pdf
Mod1_Wk2 Programming Assignment.ipynb		Mod1_Wk2 Programming Assignment.ipynb
Mod1_Wk3 Programming Assignment.ipynb		Mod1_Wk3 Programming Assignment.ipynb
Mod1_Wk4 Programming Assignment.ipynb		Mod1_Wk4 Programming Assignment.ipynb
Mod2_Capstone_Project.ipynb		Mod2_Capstone_Project.ipynb
Mod2_Capstone_Project.pdf		Mod2_Capstone_Project.pdf
Mod2_Wk1 Programming Assignment.ipynb		Mod2_Wk1 Programming Assignment.ipynb
Mod2_Wk2 Programming Assignment.ipynb		Mod2_Wk2 Programming Assignment.ipynb
Mod2_Wk3 Programming Assignment.ipynb		Mod2_Wk3 Programming Assignment.ipynb
Mod2_Wk4 Programming Assignment.ipynb		Mod2_Wk4 Programming Assignment.ipynb
Module_2_Tracking metrics in custom training loops.ipynb		Module_2_Tracking metrics in custom training loops.ipynb
README.md		README.md

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