update new libraries and links

Author: HumphreyYang

lectures/about_py.md

@@ -38,8 +38,8 @@ into R." -- Chris Wiggins
 In this lecture we will
 
 * outline what Python is
-* showcase some of its abilities
-* compare it to some other languages.
+* compare it to some other languages
+* showcase some of its abilities.
 
 At this stage, it's **not** our intention that you try to replicate all you see.
 
@@ -59,12 +59,12 @@ Python has experienced rapid adoption in the last decade and is now one of the m
 
 {index}`Python <single: Python; common uses>` is a general-purpose language used in almost all application domains such as
 
-* communications
+* finance
 * web development
 * CGI and graphical user interfaces
 * game development
-* [manufacturing resource planning](https://ieeexplore.ieee.org/abstract/document/8667819)
-* multimedia, data processing, security, etc., etc., etc.
+* manufacturing
+* multimedia, data science, security, etc., etc., etc.
 
 Used and supported extensively by Internet services and high-tech companies including
 
@@ -74,11 +74,11 @@ Used and supported extensively by Internet services and high-tech companies incl
 * [Dropbox](https://www.dropbox.com/)
 * [Reddit](https://www.reddit.com/)
 
-For reasons we will discuss, Python is particularly popular within the scientific community and behind many scientific achievements in [space science](https://code.nasa.gov/?q=python), [particle physics](https://home.cern/news/news/physics/speeding-machine-learning-particle-physics), [genomics](https://github.com/deepmind/alphafold), medical science and practically all branches of academia.
+For reasons we will discuss, Python is particularly popular within the scientific community and behind many scientific achievements in [space science](https://code.nasa.gov/?q=python), [particle physics](https://home.cern/news/news/physics/speeding-machine-learning-particle-physics), [genomics](https://github.com/deepmind/alphafold),and practically all branches of academia.
 
-Meanwhile, Python is also very beginner-friendly and is found to be suitable for students to learn programming and [introduce computational methods to students in fields other than computer science](https://www.sciencedirect.com/science/article/pii/S1477388021000177).
+Meanwhile, Python is also very beginner-friendly and is found to be suitable for students learning programming and recommended to introduce computational methods to students in [fields other than computer science](https://www.sciencedirect.com/science/article/pii/S1477388021000177).
 
-It is also [replacing familiar tools like Excel](https://www.efinancialcareers.com.au/news/2019/11/python-replaced-excel-banking) in the fields of finance and banking.
+Python is also [replacing familiar tools like Excel as a essential skill](https://www.efinancialcareers.com.au/news/2021/08/python-for-banking-jobs) in the fields of finance and banking.
 
 ### Relative Popularity
 
@@ -145,12 +145,12 @@ Python has become one of the core languages of scientific computing.
 It's either the dominant player or a major player in
 
 * [machine learning and data science](http://scikit-learn.org/stable/)
-* [natural language processing](https://www.nltk.org/)
 * [astronomy](http://www.astropy.org/)
 * [artificial intelligence](https://wiki.python.org/moin/PythonForArtificialIntelligence)
 * [chemistry](http://chemlab.github.io/chemlab/)
 * [computational biology](http://biopython.org/wiki/Main_Page)
 * [meteorology](https://pypi.org/project/meteorology/)
+* [natural language processing](https://www.nltk.org/)
 
 Its popularity in economics is also beginning to rise.
 
@@ -248,7 +248,7 @@ Other graphics libraries include
 * [seaborn](https://seaborn.pydata.org/) --- a high-level interface for matplotlib
 * [Bokeh](http://bokeh.pydata.org/en/latest/)
 
-You can visit the [Python Graph Gallery](https://www.python-graph-gallery.com/) for example plots drawn using a variety of packages.
+You can visit the [Python Graph Gallery](https://www.python-graph-gallery.com/) for more example plots drawn using a variety of libraries.
 
 ### Symbolic Algebra
 
@@ -354,12 +354,12 @@ df.mean()
 ```{index} single: PyTorch
 ```
 
-* [PyTorch](https://pytorch.org/) --- Deep learning framework in Python and other major competitors including [TensorFlow](https://www.tensorflow.org/overview) and [Keras](https://keras.io/)
+* [PyTorch](https://pytorch.org/) --- Deep learning framework in Python and other major competitors in the field including [TensorFlow](https://www.tensorflow.org/overview) and [Keras](https://keras.io/)
 
 ```{index} single: Pyro
 ```
 
-* [Pyro](https://pyro.ai/) and [PyStan](https://pystan.readthedocs.org/en/latest/) --- for Bayesian data analysis building on [Pytorch](https://pytorch.org/) and [stan](http://mc-stan.org/) respectively.
+* [Pyro](https://pyro.ai/) and [PyStan](https://pystan.readthedocs.org/en/latest/) --- for Bayesian data analysis building on [Pytorch](https://pytorch.org/) and [stan](http://mc-stan.org/) respectively
 
 ```{index} single: lifelines
 ```
@@ -369,7 +369,7 @@ df.mean()
 ```{index} single: GeoPandas
 ```
 
-*[GeoPandas](https://geopandas.org/en/stable/) --- spatial data analysis
+* [GeoPandas](https://geopandas.org/en/stable/) --- for spatial data analysis
 
 
 ### Networks and Graphs
@@ -426,16 +426,15 @@ Running your Python code on massive servers in the cloud is becoming easier and
 
 ```{index} single: cloud computing; google colab
 ```
-An excellent example of the portability of python in a cloud computing environment is The [Google Colab](https://colab.research.google.com/). It hosts the Jupyter notebook on cloud servers with no pre-configuration necessary to run Python code using cloud servers.
 
+An excellent example of the portability of python in a cloud computing environment is the [Google Colab](https://colab.research.google.com/). It hosts the Jupyter notebook on cloud servers with no pre-configuration necessary to run Python code using cloud servers.
 
-There are also commercial applications of cloud computing:
+
+There are also commercial applications of cloud computing using Python:
 
 ```{index} single: cloud computing; anaconda enterprise
 ```
-* [Anaconda Enterprise](https://www.anaconda.com/enterprise/).
-
-See also
+* [Anaconda Enterprise](https://www.anaconda.com/enterprise/)
 
 ```{index} single: cloud computing; amazon ec2
 ```
@@ -496,16 +495,30 @@ Some representative examples include
 
 * [Numba](http://numba.pydata.org/) --- make Python run at the same speed as native machine code!
 
+
 ```{index} single: scientific programming; scikit-image
 ```
 
-* [scikit-image](https://scikit-image.org/) --- handles image data for computer vision
+* [scikit-image](https://scikit-image.org/) and [OpenCV](https://opencv.org/) --- process and analyse scientific image data.
+
+
+```{index} single: scientific programming; mlflow
+```
+
+* [FLAML](https://mlflow.org/docs/latest/index.html) --- automate machine learning and hyperparameter tuning.
+
 
 ```{index} single: scientific programming; PyTables
 ```
 
 * [PyTables](http://www.pytables.org) --- manage large data sets.
 
+```{index} single: scientific programming; BeautifulSoup
+```
+
+* [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/bs4/doc/) --- process online data from HTML and XML files.
+
+
 ```{index} single: scientific programming; CVXPY
 ```