New Examples and Tutorials chapter added

Author: rkedar1

doc/documents/Examples_Tutorials/Examples_Tutorials.rst

@@ -314,6 +314,8 @@ It depends on the basic operation used by primitive:
 
    Output configurability is specified in description for each primitive.
 
+.. _quant_acc_bit_depth: 
+   
 Quantization: Influence of Accumulator Bit Depth
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 

doc/documents/MLI_FP_data_format/MLI_FP_data_format.rst

@@ -49,7 +49,7 @@ inputs shape.
 
 For more details on calculations see convolution part of `TensorFlow–Neural Network details`_. 
 
-.. _TensorFlow–Neural Network details: https://www.tensorflow.org/api_guides/python/nn.
+.. _TensorFlow–Neural Network details: https://www.tensorflow.org/versions/r1.11/api_guides/python/nn
 
 ReLU activation function might be applied to result of convolution. The
 following types of ReLU activations are supported (for more info see

doc/documents/MLI_kernels/convolution_2d.rst

@@ -34,7 +34,7 @@ padding parameters. This logic is similar to convolution 2D operation
 For more information on calculations, see the pooling part of
 `TensorFlow–Neural Network details`_.
 
-.. _TensorFlow–Neural Network details: https://www.tensorflow.org/api_guides/python/nn   
+.. _TensorFlow–Neural Network details: https://www.tensorflow.org/versions/r1.11/api_guides/python/nn   
 
 .. caution::
    Ensure that input and output