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Table of Contents

Key Points

  1. Python or R for analytics?  creating models or building models in apps?

References

...

...

Python for Java Developers - quick start

...

https://lobster1234.github.io/2017/05/25/python-java-primer/

https://drive.google.com/open?id=1bSt5RuW8VAGmpE9vYa5x-d02i7TnEyrD

python-4-java-io-lobster1234.github.io-Python Primer for Java Developers.pdf

...

https://realpython.com/oop-in-python-vs-java/

python-4-java-realpython.com-Object-Oriented Programming in Python vs Java.pdf

...

Table of Contents

Key Points

  1. Python or R for analytics?  creating models or building models in apps?


References

...

Reference_description_with_linked_URLs_______________________Notes______________________________________________________________
Python basic setup tutorial - DatacampPython install, setup, basic tutorial **
https://www.python.org/Python.org
https://docs.python.org/3/Python 3.x docs
https://wiki.python.org/moin/Python wiki
https://github.com/bcafferky/sharedBryan Cafferky's Python Spark repos **
Bryan Cafferky on youtubeBryan Python, Spark videos **
https://blog.hubspot.com/website/python-ai-libraries

Complete Guide to Python AI Libraries

https://wiki.python.org/moin/MovingToPythonFromOtherLanguagesMoving to Python from other languages


file/d/1kV1wy4-RJbGXecetFMgab_iOyI4UEFoo/view?usp=sharingPython Anaconda - miniconda distributions and key commands

Python for Java Developers - quick start

https://thevalleyofcode.com/python/ online

python-handbook.pdf file

python handbook

Python Programming for Beginners.pdf. link

Python Programming for Beginners.pdf  filelobster1234.github.io/2017/05/25/python-java-primer/

https://drive.google.com/open?id=1bSt5RuW8VAGmpE9vYa5x-d02i7TnEyrD

python-4-java-io-lobster1234.github.io-Python Primer for Java Developers.pdf

Python for Java Developers - includes file , http io

https://realpython.com/

 
Python tutorials **
https://scikit-learn.org/stable/Scikit-Learn -
https://jupyter.org/• Jupyter Notebook -

oop-in-python-vs-java/

python-4-java-realpython.com-Object-Oriented Programming in Python vs Java.pdf

Python for Java Developers - OO concepts - blog - realpython
http://anh.cs.luc.edu/170/mynotes/userdefinedjavaobjects.htmlPython to Java exercises - convert Python code to Java examples

https://

anaconda

towardsdatascience.

org/• Anaconda -

com/13-conda-commands-for-data-scientists-e443d275eb89

https://

www

drive.

kaggle

google.com/

• Kaggle -Analytics with Python or R

file/d/1kV1wy4-RJbGXecetFMgab_iOyI4UEFoo/view?usp=sharing

Python Anaconda - miniconda distributions and key commands


https://www.datacampthevalleyofcode.com/community/tutorials/r-or-python-for-data-analysis?fbclid=
IwAR3AEPrIfQrpoHPIeymv7zAPhEnrpR1RL0zZ8IS7
9AlaHgyzUPgouZmbBX4

python-vs-R-for-analytics-use-cases-2019.pdf

Python or R for analytics ?  comparison from DataCampBillable courses on Pythonhttps://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/ML and Python basics - RECOMMENDED first course

python/ online

python-handbook.pdf file

python handbook

Python Programming for Beginners.pdf. link

Python Programming for Beginners.pdf  file




https://realpython.com/ Python tutorials **
https://scikit-learn.org/stable/Scikit-Learn -
https://jupyter.org/• Jupyter Notebook -
https://anaconda.org/• Anaconda -
https://www.udemykaggle.com/course/math-with-python/learn Python and Math• Kaggle -


Analytics with Python or R


https://www.

udemy

datacamp.com/

course/pytorch-for-deep-learning-with-python-bootcamp/Pytorch intermediate

community/tutorials/r-or-python-for-data-analysis?fbclid=
IwAR3AEPrIfQrpoHPIeymv7zAPhEnrpR1RL0zZ8IS7
9AlaHgyzUPgouZmbBX4

python-vs-R-for-analytics-use-cases-2019.pdf

Python or R for analytics ?  comparison from DataCamp


Billable courses on Python
https://moriohwww.udemy.com/p/n0aRySfEzqFf?f=5c21fb01c16e2556b555ab32&fbclid=IwAR3_QQT4
yej5ns4LXwQQVrT4kH7Gkp44Gx7QvWP4ubxRT-LsvIUXmaHl4Nk
Python and MySQL TutorialDjango - python scrudcourse/python-for-data-science-and-machine-learning-bootcamp/ML and Python basics - RECOMMENDED first course


https://www.djangoprojectudemy.com/Django homecourse/math-with-python/learn Python and Math
https://www.djangoprojectudemy.com/start/Django getting started
https://docs.djangoproject.com/en/3.0/Django docs

Key Concepts

...

...


Key Concepts


Python for Java Developers Quickstart

https://medium.com/nestedif/cheatsheet-python-for-java-developers-98f75c94a1a

...

Python indexes and slices for a six-element list.
Indexes enumerate the elements, slices enumerate the spaces between the elements.

Index from rear:    -6  -5  -4  -3  -2  -1      a=[0,1,2,3,4,5]    a[1:]==[1,2,3,4,5]
Index from front:    0   1   2   3   4   5      len(a)==6          a[:5]==[0,1,2,3,4]
                   +---+---+---+---+---+---+    a[0]==0            a[:-2]==[0,1,2,3]
                   | a | b | c | d | e | f |    a[5]==5            a[1:2]==[1]
                   +---+---+---+---+---+---+    a[-1]==5           a[1:-1]==[1,2,3,4]
Slice from front:  :   1   2   3   4   5   :    a[-2]==4
Slice from rear:   :  -5  -4  -3  -2  -1   :
                                                b=a[:]
                                                b==[0,1,2,3,4,5] (shallow copy of a)
  • Lose the braces, as you know them, and most of the semicolons, obviously.
  • Backslash can be used to allow continuing the program line past a carriage-return, but you almost never have to use it. Python is smart enough to do the right thing when it sees an open bracket, a comma separated list, and a carriage-return.
  • Strings are immutable. Whenever you think you have changed a string, remember that you really created a new string.
  • Where you would use <vector T>, use lists, or tuples, that is [] or (). Where you would use <map T1, T2>, use dictionaries, that is {} .

  • The semantics of iterators is available, but most of the syntax goes away. for item in alist: iterates over all the items in alist, one by one .. where alist is a sequence, i.e. a list, tuple, or string. To iterate over a sublist, use slices: for item in alist[1:-1]: does as above, but omits the first and last items.

  • For trickier iterations, read and re-read the Library doc on the topic of general-purpose functions. There are some functions that apply to sequences: map, filter, reduce, zip. that can work wonders. Hidden somewhere under the documentation for sequences there is a description of string methods that you'll want to read.
  • Hidden under the docs for 'Other Types' are the descriptions of all the file methods. There are no iostreams per se, but the class method str can get some of the effect for your own classes, and there are surely other angles I haven't thought of.

  • Forget overloading. You can define a function, and call it with anything you want, but if it has to behave differently for different type operands, you have to use the run-time type identification type function explicitly within the single definition of the function. Default arguments to functions are just as powerful a tool as in C++. Actually polymorphism does work as expected, it just doesn't require deriving from a base class as in C++ or Java.

  • In class definitions the equivalents of operator methods are covered in a chapter in the Python Language Reference. (Look for the double-underscore methods like __cmp__, __str__, __add__, etc.)

  • In C, the gotcha for new users is probably about pointers; they're tricky and they can't be avoided. The gotchas in Python are situations when you use different references to a single object, thinking you are using different objects. I believe the difference between mutable and immutable objects comes into play. I have no clear answers here .. I still get caught once in a while .. keep your eyes open.
  • Read the Tutorial once, skim the Library Reference .. at least the table of contents, then skim the Language Reference and you will probably have encountered everything you need.
  • For reference the excellent Python Quick Reference and the Module Index of the Python docs are generally sufficient.

Python PEP 8: Style Guide for Python Code

Style Guide for Python Code

Sample Python Projects

Basic Python projects

https://morioh.com/p/f7286d9ee563?f=5c224490c513a556c9042463&fbclid=IwAR2wHrK-pi5FQ2-zH9fWgdHbu63UIa5yU0TBCwV59D4HM1HHFRG2Hd7j0so

Python and MySQL Tutorial

https://morioh.com/p/n0aRySfEzqFf?f=5c21fb01c16e2556b555ab32&fbclid=IwAR3_QQT4yej5ns4LXwQQVrT4kH7Gkp44Gx7QvWP4ubxRT-LsvIUXmaHl4Nk

sample code 

https://github.com/hnasr/python_playground/tree/master/mysqldemopython

Code Block
languagepy
titlePython and MySQL
collapsetrue
import mysql.connector

#connecting to a database
con = mysql.connector.connect(
    host = "husseinmac",
    user = "root",
    password = "password",
    database = "husseindb",
    port = 3306
)

print("Hey, I think I'm connected")

#cursor 
cur = con.cursor()
#insert a new row

for i in range(100):
    cur.execute("INSERT INTO employees (ID, NAME) VALUES (%s, %s)", (i+10, f'Mark{i}' ))

#execute the query
cur.execute("SELECT ID,NAME FROM employees")

#cur.execute("SELECT ID,NAME FROM employees where NAME = %s", ("Yara",))

rows = cur.fetchall()

for r in rows:
    print(f" ID = {r[0]} NAME = {r[1]}")

#commit the transaction
con.commit()

#close the cursor
cur.close()
#close the connection
con.close()

Simplest Neural Network in Python - Perceptron

https://morioh.com/p/512d41219fda?f=5c21fb01c16e2556b555ab32&fbclid=IwAR34w7O9dK5RtqoTryI9QI5op7UUfNXNHJ6wMz7Uenr83DdfgXbdz0Ng3Pg

In this video I'll show you how an artificial neural network works, and how to make one yourself in Python. In the next video we'll make one that is usable, but if you want, that code can already be found on github. I recommend watching at 1.5x speed, unless you're coding along.

video

Widget Connector
urlhttp://youtube.com/watch?v=kft1AJ9WVDk

video 2 

Widget Connector
urlhttp://youtube.com/watch?v=Py4xvZx-A1E

https://morioh.com/p/512d41219fda

Create a Simple Neural Network in Python from ScratchImage Removed

Github code

https://github.com/jonasbostoen/simple-neural-network

reating a simple neural network in Python with one input layer (3 inputs) and one output neuron. A neural network with no hidden layers is called a perceptron. In the training_version.py I train the neural network in the clearest way possible, but it's not really useable. The outputs of the training can be found in outputs.txt . neural_network.py is an object and can be used by giving in different inputs.

Thanks to Milo Spencer-Harber for this: https://medium.com/technology-invention-and-more/how-to-build-a-simple-neural-network-in-9-lines-of-python-code-cc8f23647ca1

And to Andrew Trask for this: https://iamtrask.github.io/2015/07/12/basic-python-network/

What does it do?

The neural_net.py tries to predict the output given 3 binary inputs. If the first input is 1, the output should be one. Otherwise the output should be 0.

...

languagepy
titlesimple neural network - perceptron
collapsetrue

Build Amazon Price Checker with Python, Selenium

https://morioh.com/p/9cb73e75c41b?f=5c224490c513a556c9042463&fbclid=IwAR108UiH8umne49I1rjG1AsfLtwIQiFBzu3_ImlKWEnZgHPns5922WNDfDY

In this FREE LIVE training, Qazi and Jakob will show you how to build an AMAZON Price Tracker with Python and Selenium 🚀

Github Repo 👉 https://github.com/jakobowsky/AmazonPriceTracker

Widget Connector
urlhttp://youtube.com/watch?v=WbJeL_Av2-Q

Screen Scrape to create Web dataset with Python, SOAP library 

https://morioh.com/p/876f3464c2d6?f=5c21f93bc16e2556b555ab2f&fbclid=IwAR3WtaWoQFVOp4Ch0_WftXHWytLd1H9yzPQMuarRWr7YgsvvZhVC9LTz1jU

...

Web Scraping with Beautiful Soap
Beautiful Soap is a Library in Python which will provide you some flexible tools to for Web Scraping. Now let’s import some necessary libraries to get started with with our task:

https://thecleverprogrammer.com/2020/07/18/web-scraping-using-python-to-create-a-dataset/?utm_source=rss&utm_medium=rss&utm_campaign=web-scraping-using-python-to-create-a-dataset

Logistic Regression Using Python 

Python Programming for Beginners - Bryan Cafferky

series

https://www.youtube.com/channel/UCEdMzQ0m9WcZQepgizrHpMw

p1 -get started

https://www.youtube.com/watch?v=iL1DJSpRxaM&t=7s

p2 - syntax

https://www.youtube.com/watch?v=Y69OtFzeY-Y&t=32s

p3 - variables

https://www.youtube.com/watch?v=oLYJIBOLfGI&t=2s

Python and SQL series - Bryan Cafferky

Python + SQL: Part 1 - The Easiest Way

https://www.youtube.com/watch?v=xY54Emo8rQM

Why use SQLite ?

https://www.youtube.com/watch?v=E7aY1XJX1og&t=147s

Using SQLite Studio

https://www.youtube.com/watch?v=dugUk893gxQ

Python and Postgres Video Series

https://www.youtube.com/watch?v=u-c6rhd8MJc

https://github.com/bcafferky/shared/tree/master/PythonPostgreSQLUpsert

Video: Using SQL with Python: Lesson 8 - Introducing PostgreSQL

...

Video: Using SQL with Python: Lesson 9 - Using PostgreSQL for Data Analysis

...

Potential Value Opportunities

Potential Challenges

...

              b=a[:]
                                                b==[0,1,2,3,4,5] (shallow copy of a)
  • Lose the braces, as you know them, and most of the semicolons, obviously.
  • Backslash can be used to allow continuing the program line past a carriage-return, but you almost never have to use it. Python is smart enough to do the right thing when it sees an open bracket, a comma separated list, and a carriage-return.
  • Strings are immutable. Whenever you think you have changed a string, remember that you really created a new string.
  • Where you would use <vector T>, use lists, or tuples, that is [] or (). Where you would use <map T1, T2>, use dictionaries, that is {} .

  • The semantics of iterators is available, but most of the syntax goes away. for item in alist: iterates over all the items in alist, one by one .. where alist is a sequence, i.e. a list, tuple, or string. To iterate over a sublist, use slices: for item in alist[1:-1]: does as above, but omits the first and last items.

  • For trickier iterations, read and re-read the Library doc on the topic of general-purpose functions. There are some functions that apply to sequences: map, filter, reduce, zip. that can work wonders. Hidden somewhere under the documentation for sequences there is a description of string methods that you'll want to read.
  • Hidden under the docs for 'Other Types' are the descriptions of all the file methods. There are no iostreams per se, but the class method str can get some of the effect for your own classes, and there are surely other angles I haven't thought of.

  • Forget overloading. You can define a function, and call it with anything you want, but if it has to behave differently for different type operands, you have to use the run-time type identification type function explicitly within the single definition of the function. Default arguments to functions are just as powerful a tool as in C++. Actually polymorphism does work as expected, it just doesn't require deriving from a base class as in C++ or Java.

  • In class definitions the equivalents of operator methods are covered in a chapter in the Python Language Reference. (Look for the double-underscore methods like __cmp__, __str__, __add__, etc.)

  • In C, the gotcha for new users is probably about pointers; they're tricky and they can't be avoided. The gotchas in Python are situations when you use different references to a single object, thinking you are using different objects. I believe the difference between mutable and immutable objects comes into play. I have no clear answers here .. I still get caught once in a while .. keep your eyes open.
  • Read the Tutorial once, skim the Library Reference .. at least the table of contents, then skim the Language Reference and you will probably have encountered everything you need.
  • For reference the excellent Python Quick Reference and the Module Index of the Python docs are generally sufficient.



Python PEP 8: Style Guide for Python Code

Style Guide for Python Code


Sample Python Projects



Basic Python projects

https://morioh.com/p/f7286d9ee563?f=5c224490c513a556c9042463&fbclid=IwAR2wHrK-pi5FQ2-zH9fWgdHbu63UIa5yU0TBCwV59D4HM1HHFRG2Hd7j0so




Python and MySQL Tutorial

https://morioh.com/p/n0aRySfEzqFf?f=5c21fb01c16e2556b555ab32&fbclid=IwAR3_QQT4yej5ns4LXwQQVrT4kH7Gkp44Gx7QvWP4ubxRT-LsvIUXmaHl4Nk



sample code 

https://github.com/hnasr/python_playground/tree/master/mysqldemopython

Code Block
languagepy
titlePython and MySQL
collapsetrue
import mysql.connector

#connecting to a database
con = mysql.connector.connect(
    host = "husseinmac",
    user = "root",
    password = "password",
    database = "husseindb",
    port = 3306
)

print("Hey, I think I'm connected")

#cursor 
cur = con.cursor()
#insert a new row

for i in range(100):
    cur.execute("INSERT INTO employees (ID, NAME) VALUES (%s, %s)", (i+10, f'Mark{i}' ))

#execute the query
cur.execute("SELECT ID,NAME FROM employees")

#cur.execute("SELECT ID,NAME FROM employees where NAME = %s", ("Yara",))

rows = cur.fetchall()

for r in rows:
    print(f" ID = {r[0]} NAME = {r[1]}")

#commit the transaction
con.commit()

#close the cursor
cur.close()
#close the connection
con.close()



Simplest Neural Network in Python - Perceptron

https://morioh.com/p/512d41219fda?f=5c21fb01c16e2556b555ab32&fbclid=IwAR34w7O9dK5RtqoTryI9QI5op7UUfNXNHJ6wMz7Uenr83DdfgXbdz0Ng3Pg

In this video I'll show you how an artificial neural network works, and how to make one yourself in Python. In the next video we'll make one that is usable, but if you want, that code can already be found on github. I recommend watching at 1.5x speed, unless you're coding along.

video

Widget Connector
urlhttp://youtube.com/watch?v=kft1AJ9WVDk

video 2 

Widget Connector
urlhttp://youtube.com/watch?v=Py4xvZx-A1E


https://morioh.com/p/512d41219fda

Create a Simple Neural Network in Python from ScratchImage Added

Github code

https://github.com/jonasbostoen/simple-neural-network

reating a simple neural network in Python with one input layer (3 inputs) and one output neuron. A neural network with no hidden layers is called a perceptron. In the training_version.py I train the neural network in the clearest way possible, but it's not really useable. The outputs of the training can be found in outputs.txt . neural_network.py is an object and can be used by giving in different inputs.

Thanks to Milo Spencer-Harber for this: https://medium.com/technology-invention-and-more/how-to-build-a-simple-neural-network-in-9-lines-of-python-code-cc8f23647ca1

And to Andrew Trask for this: https://iamtrask.github.io/2015/07/12/basic-python-network/

What does it do?

The neural_net.py tries to predict the output given 3 binary inputs. If the first input is 1, the output should be one. Otherwise the output should be 0.


Code Block
languagepy
titlesimple neural network - perceptron
collapsetrue


Build Amazon Price Checker with Python, Selenium

https://morioh.com/p/9cb73e75c41b?f=5c224490c513a556c9042463&fbclid=IwAR108UiH8umne49I1rjG1AsfLtwIQiFBzu3_ImlKWEnZgHPns5922WNDfDY

In this FREE LIVE training, Qazi and Jakob will show you how to build an AMAZON Price Tracker with Python and Selenium 🚀

Github Repo 👉 https://github.com/jakobowsky/AmazonPriceTracker

Widget Connector
urlhttp://youtube.com/watch?v=WbJeL_Av2-Q


Screen Scrape to create Web dataset with Python, SOAP library 

https://morioh.com/p/876f3464c2d6?f=5c21f93bc16e2556b555ab2f&fbclid=IwAR3WtaWoQFVOp4Ch0_WftXHWytLd1H9yzPQMuarRWr7YgsvvZhVC9LTz1jU


Web Scraping using Python To Create a Dataset | Data Science | Machine Learning | Python
In this article I will show you how you can create your own dataset by Web Scraping using Python. Web Scraping means to extract a set of data from web. If you are a programmer, a Data Scientist, Engineer or anyone who works by manipulating the data, the skills of Web Scrapping will help you in your career. Suppose you are working on a project where no data is available, then how you are going to collect the data. In this situation Web Scraping skills will help you.

Web Scraping with Beautiful Soap
Beautiful Soap is a Library in Python which will provide you some flexible tools to for Web Scraping. Now let’s import some necessary libraries to get started with with our task:

https://thecleverprogrammer.com/2020/07/18/web-scraping-using-python-to-create-a-dataset/?utm_source=rss&utm_medium=rss&utm_campaign=web-scraping-using-python-to-create-a-dataset


Logistic Regression Using Python 


Python Libraries


https://blog.hubspot.com/website/python-ai-libraries


Introduction-To-Python.pdf.  link



Python Programming for Beginners - Bryan Cafferky


series

https://www.youtube.com/channel/UCEdMzQ0m9WcZQepgizrHpMw


p1 -get started

https://www.youtube.com/watch?v=iL1DJSpRxaM&t=7s


p2 - syntax

https://www.youtube.com/watch?v=Y69OtFzeY-Y&t=32s


p3 - variables

https://www.youtube.com/watch?v=oLYJIBOLfGI&t=2s


Python and SQL series - Bryan Cafferky


Python + SQL: Part 1 - The Easiest Way

https://www.youtube.com/watch?v=xY54Emo8rQM


Why use SQLite ?

https://www.youtube.com/watch?v=E7aY1XJX1og&t=147s


Using SQLite Studio

https://www.youtube.com/watch?v=dugUk893gxQ


Python and Postgres Video Series

https://www.youtube.com/watch?v=u-c6rhd8MJc

https://github.com/bcafferky/shared/tree/master/PythonPostgreSQLUpsert


Video: Using SQL with Python: Lesson 8 - Introducing PostgreSQL
Video: Using SQL with Python: Lesson 9 - Using PostgreSQL for Data Analysis
SHOW LESS

Potential Value Opportunities



Potential Challenges



Candidate Solutions



The Quick Python Book, Fourth Edition“ by Naomi Ceder - review

Dunja Nikitovic <duni@manning.com>

We believe your insights could significantly enhance the review process, as you seem to fit with the target audience. 
You can read more about the book here.
If you are not familiar with the process yet, manuscript reviewers read chapter drafts and provide feedback to help us and the authors improve them. They comment on the writing, technical content, examples, source code, Table of Contents, and even offer their opinions on the state of the technology or reader needs.
We have chapters 1-17 with approximately 334 pages ready for the second review and the feedback should be submitted by August 26th 2024.

Please let me know if you would like to take part in the review and I will share review instructions.
book
code 


Thank you for joining us in this review, your support means a lot to us.


Chapters 1-17 from "The Quick Python Book, Fourth Edition" by Naomi Ceder are ready for the second review. More information about the book and its full table of contents is available here

The due date for submitting the feedback is August 26th 2024.    
If you see that you won’t be able to provide feedback, or that you could use more time to review, let me know as soon as you can!


The manuscript is available on the following link. You need to sign in with your Manning account to access it:

https://livebook.manning.com/book/ceder5/chapter-1/r-2

You leave comments in the manuscript by selecting a word, sentence, or a paragraph and choosing the "Annotate" icon. Also, you can rate individual figures, listings, code snippets or sections by clicking "like", "don't like" or "neutral" icons below them and leaving the comment.

While you read, or at the end of the review, 
you should fill the manuscript review questionnaire available at any moment on the following link:

Please do not comment on typos, grammar/style errors, hand-drawn graphics, etc. The manuscript will be copy edited, proof read and typeset in the later stages of production.

By accessing the manuscript you agree that you will not duplicate it or use the material to create a similar book nor discuss its contents with potential authors of similar books until this book is published or canceled.

We are making all reviews anonymous to obtain more constructive comments. Your review will be made anonymous prior to submitting to the author.
We -- that is the publisher and the author -- appreciate your assistance in making this book as useful as possible to its readers.

Thank you and kind regards,
Dunja

--

Dunja Nikitović
Review Editor
Manning Publications


Step-by-step guide for Example

...