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templates/about.md

@@ -5,22 +5,22 @@ It was developed with a focus on enabling fast experimentation. *Being able to g
 
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-## Keras & TensorFlow 2.0
+## Keras & TensorFlow 2
 
-[TensorFlow 2.0](https://www.tensorflow.org/) is an end-to-end, open-source machine learning platform. You can think of it as an infrastructure layer for
+[TensorFlow 2](https://www.tensorflow.org/) is an end-to-end, open-source machine learning platform. You can think of it as an infrastructure layer for
 [differentiable programming](https://en.wikipedia.org/wiki/Differentiable_programming). It combines four key abilities:
 
 - Efficiently executing low-level tensor operations on CPU, GPU, or TPU.
 - Computing the gradient of arbitrary differentiable expressions.
 - Scaling computation to many devices (e.g. the [Summit supercomputer](https://www.olcf.ornl.gov/summit/) at Oak Ridge National Lab, which spans 27,000 GPUs).
 - Exporting programs ("graphs") to external runtimes such as servers, browsers, mobile and embedded devices.
 
-Keras is the high-level API of TensorFlow 2.0: an approchable, highly-productive interface for solving machine learning problems,
+Keras is the high-level API of TensorFlow 2: an approchable, highly-productive interface for solving machine learning problems,
 with a focus on modern deep learning. It provides essential abstractions and building blocks for developing
 and shipping machine learning solutions with high iteration velocity.
 
 Keras empowers engineers and researchers to take full advantage of the scalability
-and cross-platform capabilities of TensorFlow 2.0: you can run Keras on TPU or on large clusters of GPUs,
+and cross-platform capabilities of TensorFlow 2: you can run Keras on TPU or on large clusters of GPUs,
 and you can export your Keras models to run in the browser or on a mobile device. 
 
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@@ -130,8 +130,8 @@ For more in-depth tutorials about Keras, you can check out:
 
 ## Installation & compatibility
 
-Keras comes packaged with TensorFlow 2.0 as `tensorflow.keras`.
-To start using Keras, simply [install TensorFlow 2.0](https://www.tensorflow.org/install).
+Keras comes packaged with TensorFlow 2 as `tensorflow.keras`.
+To start using Keras, simply [install TensorFlow 2](https://www.tensorflow.org/install).
 
 Keras/TensorFlow are compatible with:
 

templates/why_keras.md

@@ -31,16 +31,14 @@ Keras ranked as #1 for deep learning both among primary frameworks and among all
 ## Keras has broad adoption in the industry and the research community
 
 
-With over 375,000 individual users as of early 2020, Keras has strong adoption across both the industry and the research community. Together with TensorFlow 2.0, Keras has more adoption than any other deep learning solution -- in every vertical.
+With over 400,000 individual users as of early 2021, Keras has strong adoption across both the industry and the research community. Together with TensorFlow 2, Keras has more adoption than any other deep learning solution -- in every vertical.
 
 You are already constantly interacting with features built with Keras -- it is in use at Netflix, Uber, Yelp, Instacart, Zocdoc, Square, and many others. It is especially popular among startups that place deep learning at the core of their products.
 
-Keras & TensorFlow 2.0 are also a favorite among researchers, coming in #1 in terms of mentions in scientific papers indexed by Google Scholar. Keras has also been adopted by researchers at large scientific organizations, such as CERN and NASA.
+Keras & TensorFlow 2 are also a favorite among researchers, coming in #1 in terms of mentions in scientific papers indexed by Google Scholar. Keras has also been adopted by researchers at large scientific organizations, such as CERN and NASA.
 
 
-![Daily PyPI downloads](/img/graph-downloads.jpg)
-
-![Weekly Google Scholar articles](/img/graph-scholar.jpeg)
+![2020 deep learning frameworks adoption metrics](/img/deep_learning_frameworks_adoption_2020.png)
 
 
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@@ -88,7 +86,3 @@ Keras is at the center of a wide ecosystem of tightly-connected projects that to
 - Model deployment in the browser via [TF.js](https://www.tensorflow.org/js)
 - ...and many more.
 
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