remove nbviewer

Author: matbesancon

docs/src/examples/autotuning-ridge.jl

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 # # Auto-tuning Hyperparameters
 
 #md # [![](https://img.shields.io/badge/show-github-579ACA.svg)](@__REPO_ROOT_URL__/docs/src/examples/autotuning-ridge.jl)
-#md # [![](https://img.shields.io/badge/show-nbviewer-579ACA.svg)](@__NBVIEWER_ROOT_URL__/generated/autotuning-ridge.ipynb)
 
 # This example shows how to learn a hyperparameter in Ridge Regression using a gradient descent routine.
 # Let the regularized regression problem be formulated as:

docs/src/examples/chainrules_unit.jl

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 # # ChainRules integration demo: Relaxed Unit Commitment
 
 #md # [![](https://img.shields.io/badge/show-github-579ACA.svg)](@__REPO_ROOT_URL__/docs/src/examples/chainrules_unit.jl)
-#md # [![](https://img.shields.io/badge/show-nbviewer-579ACA.svg)](@__NBVIEWER_ROOT_URL__/generated/chainrules_unit.ipynb)
 
 
 # In this example, we will demonstrate the integration of DiffOpt with

docs/src/examples/custom-relu.jl

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 # # Custom ReLU layer
 
 #md # [![](https://img.shields.io/badge/show-github-579ACA.svg)](@__REPO_ROOT_URL__/docs/src/examples/custom-relu.jl)
-#md # [![](https://img.shields.io/badge/show-nbviewer-579ACA.svg)](@__NBVIEWER_ROOT_URL__/generated/custom-relu.ipynb)
 
 # We demonstrate how DiffOpt can be used to generate a simple neural network
 # unit - the ReLU layer. A neural network is created using Flux.jl which is

docs/src/examples/matrix-inversion-manual.jl

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 # # Differentiating a QP wrt a single variable
 
 #md # [![](https://img.shields.io/badge/show-github-579ACA.svg)](@__REPO_ROOT_URL__/docs/src/examples/matrix-inversion-manual.jl)
-#md # [![](https://img.shields.io/badge/show-nbviewer-579ACA.svg)](@__NBVIEWER_ROOT_URL__/generated/matrix-inversion-manual.ipynb)
-
 
 # Consider the quadratic program
 

docs/src/examples/sensitivity-analysis-ridge.jl

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 # # Sensitivity Analysis of Ridge Regression
 
 #md # [![](https://img.shields.io/badge/show-github-579ACA.svg)](@__REPO_ROOT_URL__/docs/src/examples/sensitivity-analysis-ridge.jl)
-#md # [![](https://img.shields.io/badge/show-nbviewer-579ACA.svg)](@__NBVIEWER_ROOT_URL__/generated/sensitivity-analysis-ridge.ipynb)
 
 # This example illustrates the sensitivity analysis of data points in a
 # [Ridge Regression](https://en.wikipedia.org/wiki/Ridge_regression) problem.

docs/src/examples/sensitivity-analysis-svm.jl

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 # # Sensitivity Analysis of SVM
 
 #md # [![](https://img.shields.io/badge/show-github-579ACA.svg)](@__REPO_ROOT_URL__/docs/src/examples/sensitivity-analysis-svm.jl)
-#md # [![](https://img.shields.io/badge/show-nbviewer-579ACA.svg)](@__NBVIEWER_ROOT_URL__/generated/sensitivity-analysis-svm.ipynb)
-
 
 # This notebook illustrates sensitivity analysis of data points in a [Support Vector Machine](https://en.wikipedia.org/wiki/Support-vector_machine) (inspired from [@matbesancon](http://github.com/matbesancon)'s [SimpleSVMs](http://github.com/matbesancon/SimpleSVMs.jl).)