Update README.md (pytorch#43100)

Summary:
The changes are minor.
1. Add back the external links so that readers can find out more about external tools on how to accelerate PyTorch.
2. Fix typo

Pull Request resolved: pytorch#43100

Reviewed By: colesbury

Differential Revision: D23192251

Pulled By: mrshenli

fbshipit-source-id: dde54b7942ebff5bbe3d58ad95744c6d95fe60fe

README.md

@@ -91,7 +91,7 @@ PyTorch is not a Python binding into a monolithic C++ framework.
 It is built to be deeply integrated into Python.
 You can use it naturally like you would use [NumPy](https://www.numpy.org/) / [SciPy](https://www.scipy.org/) / [scikit-learn](https://scikit-learn.org) etc.
 You can write your new neural network layers in Python itself, using your favorite libraries
-and use packages such as Cython and Numba.
+and use packages such as [Cython](https://cython.org/) and [Numba](http://numba.pydata.org/).
 Our goal is to not reinvent the wheel where appropriate.
 
 ### Imperative Experiences
@@ -105,7 +105,7 @@ We hope you never spend hours debugging your code because of bad stack traces or
 ### Fast and Lean
 
 PyTorch has minimal framework overhead. We integrate acceleration libraries
-such as [Intel MKL](https://software.intel.com/mkl) and NVIDIA (cuDNN, NCCL) to maximize speed.
+such as [Intel MKL](https://software.intel.com/mkl) and NVIDIA ([cuDNN](https://developer.nvidia.com/cudnn), [NCCL](https://developer.nvidia.com/nccl)) to maximize speed.
 At the core, its CPU and GPU Tensor and neural network backends
 (TH, THC, THNN, THCUNN) are mature and have been tested for years.
 
@@ -135,7 +135,7 @@ Commands to install from binaries via Conda or pip wheels are on our website:
 [https://pytorch.org](https://pytorch.org)
 
 
-#### NVIDIA Jetson platforms
+#### NVIDIA Jetson Platforms
 
 Python wheels for NVIDIA's Jetson Nano, Jetson TX2, and Jetson AGX Xavier are available via the following URLs:
 
@@ -342,7 +342,8 @@ Three pointers to get you started:
 * forums: discuss implementations, research, etc. https://discuss.pytorch.org
 * GitHub issues: bug reports, feature requests, install issues, RFCs, thoughts, etc.
 * Slack: The [PyTorch Slack](https://pytorch.slack.com/) hosts a primary audience of moderate to experienced PyTorch users and developers for general chat, online discussions, collaboration etc. If you are a beginner looking for help, the primary medium is [PyTorch Forums](https://discuss.pytorch.org). If you need a slack invite, please fill this form: https://goo.gl/forms/PP1AGvNHpSaJP8to1
-* newsletter: no-noise, one-way email newsletter with important announcements about pytorch. You can sign-up here: https://eepurl.com/cbG0rv
+* newsletter: no-noise, one-way email newsletter with important announcements about PyTorch. You can sign-up here: https://eepurl.com/cbG0rv
+* Facebook page: important announcements about PyTorch. https://www.facebook.com/pytorch
 * for brand guidelines, please visit our website at [pytorch.org](https://pytorch.org/)
 
 ## Releases and Contributing