Update README.md

Order packages by name and add missing descriptions.

README.md

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 JupyterLab Notebook Docker Image tailored for [Mesosphere DC/OS](https://dcos.io)
 
 Docker images built with the `Dockerfile` herein will enable support for:
-* [JupyterLab](https://jupyterlab.readthedocs.io)
+* [Apache Spark](https://spark.apache.org)
+Apache Spark™ is a unified analytics engine for large-scale data processing.
 * [BeakerX](http://beakerx.com)
 BeakerX is a collection of kernels and extensions to the Jupyter interactive computing environment. It provides JVM support, Spark cluster support, polyglot programming, interactive plots, tables, forms, publishing, and more.
-* [Tensorflow](https://www.tensorflow.org)
-* [Apache Spark](https://spark.apache.org)
-* [TensorFlowOnSpark](https://github.com/yahoo/TensorFlowOnSpark)
-* [Ray](https://ray.readthedocs.io)
-Ray is a flexible, high-performance distributed execution framework.
-Ray Tune: Hyperparameter Optimization Framework
-Ray RLlib: Scalable Reinforcement Learning
 * [Dask](https://dask.readthedocs.io)
 Dask is a flexible parallel computing library for analytic computing.
 * [Distributed](https://distributed.readthedocs.io)
 Dask.distributed is a lightweight library for distributed computing in Python. It extends both the concurrent.futures and dask APIs to moderate sized clusters.
+* [JupyterLab](https://jupyterlab.readthedocs.io)
+JupyterLab is the next-generation web-based user interface for [Project Jupyter](https://jupyter.org).
+* [PyTorch](https://pytorch.org)
+Tensors and Dynamic neural networks in Python with strong GPU acceleration. PyTorch is a deep learning framework for fast, flexible experimentation.
+* [Ray](https://ray.readthedocs.io)
+Ray is a flexible, high-performance distributed execution framework.
+  * Ray Tune: Hyperparameter Optimization Framework
+  * Ray RLlib: Scalable Reinforcement Learning
+* [Tensorflow](https://www.tensorflow.org)
+TensorFlow™ is an open source software library for high performance numerical computation.
+* [TensorFlowOnSpark](https://github.com/yahoo/TensorFlowOnSpark)
+TensorFlowOnSpark brings TensorFlow programs onto Apache Spark clusters.
 * [XGBoost](https://xgboost.ai)
-Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
+Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more.
 
 Also includes support for:
 * OpenID Connect Authentication and Authorization based on email address or User Principal Name (UPN) (for Windows Integrated Authentication and AD FS 4.0 with Windows Server 2016)
@@ -29,14 +35,14 @@ Also includes support for:
 Pre-built JupyterLab Docker Images for Mesosphere DC/OS: https://hub.docker.com/r/dcoslabs/dcos-jupyter/tags/
 
 Related Docker Images:
-- Machine Learning Worker on Mesosphere DC/OS https://hub.docker.com/r/dcoslabs/dcos-ml-worker/tags/
-- Apache Spark (with GPU support) on Mesosphere DC/OS: https://hub.docker.com/r/dcoslabs/dcos-spark/tags/
+* Machine Learning Worker on Mesosphere DC/OS: https://hub.docker.com/r/dcoslabs/dcos-ml-worker/tags/
+* Apache Spark (with GPU support) on Mesosphere DC/OS: https://hub.docker.com/r/dcoslabs/dcos-spark/tags/
 
 Built `FROM:` [debian:jessie](https://hub.docker.com/r/library/debian) with [Miniconda3](https://repo.continuum.io/miniconda/)
 
 Made possible by and/or for:
-- [Mesosphere DC/OS](https://dcos.io)
-- [Mesosphere DC/OS Enterprise](https://mesosphere.com/product)
-- [Conda](https://conda.io)
-- [Anaconda](https://www.anaconda.com)
-- [Debian](https://www.debian.org)
+* [Mesosphere DC/OS](https://dcos.io)
+* [Mesosphere DC/OS Enterprise](https://mesosphere.com/product)
+* [Conda](https://conda.io)
+* [Anaconda](https://www.anaconda.com)
+* [Debian](https://www.debian.org)