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fix README.md spelling, wording #20

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5f8d63a
fix README.md spelling, wording
ernstklrb Sep 23, 2020
bfe68f5
remove (my) clumsy range-over-to construct
ernstklrb Sep 24, 2020
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10 changes: 5 additions & 5 deletions README.md
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Expand Up @@ -17,9 +17,9 @@ instance, in an object recognition network, an attribution method could tell us
which pixels of the image were responsible for a certain label being picked, or
which words from sentence were indicative of strong sentiment.

Applications range from helping a developer debug, allowing analysts to explore
the logic of a network, and to give end-user’s some transparency into the reason
for a network’s prediction.
Applications include helping developers debug their models, allowing analysts
to explore the logic of a model, and giving end-users some transparency into the
reason for a network's prediction.

**Integrated Gradients** is a variation on computing the gradient of the
prediction output w.r.t. features of the input. It requires no modification to
Expand All @@ -44,14 +44,14 @@ deep models (sparse and dense, text and vision).
This [How-To document][howto] describes the steps involved in implementing integrated gradients
for an arbitrary deep network.

This repository provideds code for implementing integrated gradients for networks
This repository provides code for implementing integrated gradients for networks
with image inputs. It is structured as follows:
* [Integrated Gradients library][intgrad-lib]: Library implementing the core
integrated gradients algorithm.
* [Visualization library][vis-lib]: Library implementing methods for visualizing
atributions for image models.
* [Inception notebook][incp-notebook]: A [Jupyter](http://jupyter.org/) notebook
for generating and visualizing atributions for the [Inception (v1)][incp-paper]
for generating and visualizing attributions for the [Inception (v1)][incp-paper]
object recognition network.

We recommend starting with the notebook. To run the notebook, please follow the following instructions.
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