ProgrammingUltimate Guide | Intro to Python - 300+ Project Ideas
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ProgrammingUltimate Guide | Intro to Python - 300+ Project IdeasPosted:

SiDev
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Welcome to SiDev's Ultimate Python Guide
I hope you enjoy. Please provide feedback below.




Introduction

This will be a comprehensive thread on everything Python. It will touch base on libraries, AI/Machine Learning, data manipulation, and more. The information in this thread has been gathered via multiple online sources. These sources will be cited within the thread or towards the bottom. I do not claim to be the source of this information; just the messenger.

The goal of this post is to help you start down the rabbit hole that is known as Python. There are so many things that you can do with it. This post is to help provide you with the materials to get an idea of what is possible with this versatile language. I genuinely hope this post inspires someone to start their first python project or that they can say they have learned something from this post.

If you have a question on a section or need clarity on a portion of the thread, please let me know below.





Table of Contents

  • 1.0 | Setting up your Python Environment
  • 2.0 | Different IDEs
  • 3.0 | Python Capabilities & Projects
  • 4.0 | Libraries
  • 4.1 | Installing Libraries
  • 4.2 | Specific Libraries
  • 5.0 | Machine Learning / Artificial Intelligence
  • 5.1 | What is AI / Machine Learning?
  • 5.2 | TensorFlow / PyTorch / Keras
  • 5.3 | Tutorials
  • 6.0 | Data
  • 6.1 | Data Analysis / Manipulation
  • 6.2 | Data Visualization
  • 7.0 | General Resources
  • 7.1 | Useful Links
  • 7.2 | YouTube Walkthrough Playlists
  • 8.0 | Jupyter Notebook
  • 8.1 | Getting Started / What is Jupyter Notebook?
  • 8.2 | Using the Notebook
  • 8.3 | Reference Projects
  • 9.0 | Community Feedback / Involvement
  • 9.1 | Suggestions for Thread Additions
  • 9.2 | Python Support
  • 10.0 | Discord Bots / Discord.py - COMING SOON
  • 11.0 | Closing Remarks





1.0 | Setting up your Python Environment

You will need to setup your python environment before proceeding any further. Below is a text tutorial and a video tutorial, depending on your preference.

Text tutorial where you can follow along.






2.0 | Different IDEs

Jupyter Notebooks
PyCharm
VSCode
Notepad++

There are more available IDEs but these seem to be the most popular. Each have their own pro's and con's which will be added to this post at a later date. Feel each of them out and choose the one you like most.





3.0 | Python Capabilities & Project Ideas






4.0 | Libraries
4.1 | Installing Libraries

Just like you installed your python environment, you must install a library to be able to use it.

Following along to a text step-by-step tutoral.



4.2 | Specific Libraries

  • Matplotlib
    Matplotlib helps with data analyzing, and is a numerical plotting library. It also provides amazing data visualization features.

  • Pandas
    Pandas is a must for data science. It provides fast, expressive,, and flexible data structures to easily work with structured and time-series data.

  • HTTP Requests
    Requests allows you to send HTTP/1.1 requests, add headers, form data, multipart files, and parameters.

  • NumPy
    NumPy has advanced math functions and a rudimentary scientific computing package.

  • BeautifulSoup
    BeautifulSoup is a slower XML/HTML parsing library for beginners.

  • PyGame
    PyGame provides an extremely easy interface to the Simple Directmedia Library (SDL) platform-independent graphic, audio, and input libraries.

  • TensorFlow
    TensorFlow is a library used for AI/machine learning models.

  • Other Notable Python Libraries & Source of information


I will do a more post to go more in-depth on libraries and their unique features in a later post.





5.0 | Machine Learning / Artificial Intelligence

5.1 | What is AI / Machine Learning?

What Is Artificial Intelligence?

Artificial Intelligence is the field of developing computers and robots that are capable of behaving in ways that both mimic and go beyond human capabilities. AI-enabled programs can analyze and contextualize data to provide information or automatically trigger actions without human interference.

Today, artificial intelligence is at the heart of many technologies we use, including smart devices and voice assistants such as Siri on Apple devices. Companies are incorporating techniques such as natural language processing and computer vision -- the ability for computers to use human language and interpret images -- to automate tasks, accelerate decision making, and enable customer conversations with chatbots.

What Is Machine Learning?

Machine learning is a pathway to artificial intelligence. This subcategory of AI uses algorithms to automatically learn insights and recognize patterns from data, applying that learning to make increasingly better decisions.

By studying and experimenting with machine learning, programmers test the limits of how much they can improve the perception, cognition, and action of a computer system.

Deep learning, an advanced method of machine learning, goes a step further. Deep learning models use large neural networks -- networks that function like a human brain to logically analyze data -- to learn complex patterns and make predictions independent of human input.


5.2 | TensorFlow / PyTorch / Keras



These 3 libraries are the leaders in AI / machine learning. They each have their own strengths in certain areas and weaknesses in others. These links do a good job at comparing each of them to give you the proper information to decide which library or libraries will work best for your particular project.



5.3 | Tutorials







6.0 | Data






7.0 | General Resources






8.0 | Jupyter's Notebook
8.1 | Getting Started / What is Jupyter Notebook?
Project Jupyter builds tools, standards, and services for many different use cases. This page has links to interactive demos that allow you to try some our tools for free online, thanks to mybinder.org, a free public service provided by the Jupyter community.




8.2 | Using the Notebook


8.3 | Reference Projects






9.0 | Community Feedback / Involvement
9.1 | Suggestions for Thread Additions
I have tried to incorporate as much information as I possibly can into this one post. This information has taken days to compile into one post. I have barely even touched the surface with what is possible with Python in this thread.

If you liked this thread and have learned something from it, I will continue to make threads similar to this to drill down on topics of interest. I would like to hear from the TTG community on which topics you would like covered. Post any suggestions as a reply down below.

If you are a fellow programmer, please point out anything I missed as I would like this thread to be a one-stop-shop for all information regarding Python. The more information, the better.


9.2 | Python Support
As stated above, the goal of this thread is to inspire people to get their feet wet with Python. You guys will run into errors and roadblocks. Post the errors here as reply. Let myself and the community help you on this thread. If you need assistance with a Python project that is not listed above, please post about it below for help. I will monitor this thread and help each and every person I can if they post their errors in here.






10.0 | Discord Bots / Discord.py
COMING SOON





11.0 | Closing Remarks
First off, I want to say thank you to anyone and everyone who took the time to read this thread in its entirety. It took me almost a week to get this thread how I wanted. I still consider it unfinished. There is still more I want to add and will add. I look forward to hearing feedback and thoughts from the community.

I hope this thread inspires someone in the community to learn more about python and programming in general. I hope this thread can stand as resource for all and act as a place of support for many.

Thank you all for your time.

- SiDev -


Last edited by SiDev ; edited 10 times in total

The following 2 users thanked SiDev for this useful post:

Nathan (02-23-2023), Chosen (02-21-2023)
#2. Posted:
Chosen
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Very nice thread SiDev, lots of good information here.
#3. Posted:
SiDev
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Chosen wrote Very nice thread SiDev, lots of good information here.


Thank you, kind sir.
#4. Posted:
RiddIer
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Reading Python code looks like reading a regular book if coded correctly. The syntax is awesome, though I would not recommend learning it if it is your first language, you miss out on too many intricacies and small details if you are serious about learning.

Great post overall! Though the purple font on dark mode makes it hard to read with my old eyes
#5. Posted:
SiDev
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Joined: Dec 13, 20203Year Member
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RiddIer wrote Reading Python code looks like reading a regular book if coded correctly. The syntax is awesome, though I would not recommend learning it if it is your first language, you miss out on too many intricacies and small details if you are serious about learning.

Great post overall! Though the purple font on dark mode makes it hard to read with my old eyes


100% Agreed and very well said. Personally, I think a language such as Java or C# prove to be solid choices for a first language in my opinion.
#6. Posted:
RiddIer
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SiDev wrote
RiddIer wrote Reading Python code looks like reading a regular book if coded correctly. The syntax is awesome, though I would not recommend learning it if it is your first language, you miss out on too many intricacies and small details if you are serious about learning.

Great post overall! Though the purple font on dark mode makes it hard to read with my old eyes


100% Agreed and very well said. Personally, I think a language such as Java or C# prove to be solid choices for a first language in my opinion.


Or just be a gigachad and learn C first

(this is a joke, no one learn C as a first language)
#7. Posted:
SiDev
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Status: Offline
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Status: Offline
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Section dedicated for python discord bots coming soon.
#8. Posted:
Cybersified
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This Thread is very clean and well put together, Love the simplicity. Keep up the great work.
#9. Posted:
Polaris-
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Overall this is great, it's all mostly the main basics and understanding to Python, however you should add some more context instead of hiding them in spoliers, and give each their own statement of their courses/test and tutorials.

Great work.

SiDev wrote
Welcome to SiDev's Ultimate Python Guide
I hope you enjoy. Please provide feedback below.




Introduction

This will be a comprehensive thread on everything Python. It will touch base on libraries, AI/Machine Learning, data manipulation, and more. The information in this thread has been gathered via multiple online sources. These sources will be cited within the thread or towards the bottom. I do not claim to be the source of this information; just the messenger.

The goal of this post is to help you start down the rabbit hole that is known as Python. There are so many things that you can do with it. This post is to help provide you with the materials to get an idea of what is possible with this versatile language. I genuinely hope this post inspires someone to start their first python project or that they can say they have learned something from this post.

If you have a question on a section or need clarity on a portion of the thread, please let me know below.





Table of Contents

  • 1.0 | Setting up your Python Environment
  • 2.0 | Different IDEs
  • 3.0 | Python Capabilities & Projects
  • 4.0 | Libraries
  • 4.1 | Installing Libraries
  • 4.2 | Specific Libraries
  • 5.0 | Machine Learning / Artificial Intelligence
  • 5.1 | What is AI / Machine Learning?
  • 5.2 | TensorFlow / PyTorch / Keras
  • 5.3 | Tutorials
  • 6.0 | Data
  • 6.1 | Data Analysis / Manipulation
  • 6.2 | Data Visualization
  • 7.0 | General Resources
  • 7.1 | Useful Links
  • 7.2 | YouTube Walkthrough Playlists
  • 8.0 | Jupyter Notebook
  • 8.1 | Getting Started / What is Jupyter Notebook?
  • 8.2 | Using the Notebook
  • 8.3 | Reference Projects
  • 9.0 | Community Feedback / Involvement
  • 9.1 | Suggestions for Thread Additions
  • 9.2 | Python Support
  • 10.0 | Discord Bots / Discord.py - COMING SOON
  • 11.0 | Closing Remarks





1.0 | Setting up your Python Environment

You will need to setup your python environment before proceeding any further. Below is a text tutorial and a video tutorial, depending on your preference.

Text tutorial where you can follow along.






2.0 | Different IDEs

Jupyter Notebooks
PyCharm
VSCode
Notepad++

There are more available IDEs but these seem to be the most popular. Each have their own pro's and con's which will be added to this post at a later date. Feel each of them out and choose the one you like most.





3.0 | Python Capabilities & Project Ideas






4.0 | Libraries
4.1 | Installing Libraries

Just like you installed your python environment, you must install a library to be able to use it.

Following along to a text step-by-step tutoral.



4.2 | Specific Libraries

  • Matplotlib
    Matplotlib helps with data analyzing, and is a numerical plotting library. It also provides amazing data visualization features.

  • Pandas
    Pandas is a must for data science. It provides fast, expressive,, and flexible data structures to easily work with structured and time-series data.

  • HTTP Requests
    Requests allows you to send HTTP/1.1 requests, add headers, form data, multipart files, and parameters.

  • NumPy
    NumPy has advanced math functions and a rudimentary scientific computing package.

  • BeautifulSoup
    BeautifulSoup is a slower XML/HTML parsing library for beginners.

  • PyGame
    PyGame provides an extremely easy interface to the Simple Directmedia Library (SDL) platform-independent graphic, audio, and input libraries.

  • TensorFlow
    TensorFlow is a library used for AI/machine learning models.

  • Other Notable Python Libraries & Source of information


I will do a more post to go more in-depth on libraries and their unique features in a later post.





5.0 | Machine Learning / Artificial Intelligence

5.1 | What is AI / Machine Learning?

What Is Artificial Intelligence?

Artificial Intelligence is the field of developing computers and robots that are capable of behaving in ways that both mimic and go beyond human capabilities. AI-enabled programs can analyze and contextualize data to provide information or automatically trigger actions without human interference.

Today, artificial intelligence is at the heart of many technologies we use, including smart devices and voice assistants such as Siri on Apple devices. Companies are incorporating techniques such as natural language processing and computer vision -- the ability for computers to use human language and interpret images -- to automate tasks, accelerate decision making, and enable customer conversations with chatbots.

What Is Machine Learning?

Machine learning is a pathway to artificial intelligence. This subcategory of AI uses algorithms to automatically learn insights and recognize patterns from data, applying that learning to make increasingly better decisions.

By studying and experimenting with machine learning, programmers test the limits of how much they can improve the perception, cognition, and action of a computer system.

Deep learning, an advanced method of machine learning, goes a step further. Deep learning models use large neural networks -- networks that function like a human brain to logically analyze data -- to learn complex patterns and make predictions independent of human input.


5.2 | TensorFlow / PyTorch / Keras



These 3 libraries are the leaders in AI / machine learning. They each have their own strengths in certain areas and weaknesses in others. These links do a good job at comparing each of them to give you the proper information to decide which library or libraries will work best for your particular project.



5.3 | Tutorials







6.0 | Data






7.0 | General Resources






8.0 | Jupyter's Notebook
8.1 | Getting Started / What is Jupyter Notebook?
Project Jupyter builds tools, standards, and services for many different use cases. This page has links to interactive demos that allow you to try some our tools for free online, thanks to mybinder.org, a free public service provided by the Jupyter community.




8.2 | Using the Notebook


8.3 | Reference Projects






9.0 | Community Feedback / Involvement
9.1 | Suggestions for Thread Additions
I have tried to incorporate as much information as I possibly can into this one post. This information has taken days to compile into one post. I have barely even touched the surface with what is possible with Python in this thread.

If you liked this thread and have learned something from it, I will continue to make threads similar to this to drill down on topics of interest. I would like to hear from the TTG community on which topics you would like covered. Post any suggestions as a reply down below.

If you are a fellow programmer, please point out anything I missed as I would like this thread to be a one-stop-shop for all information regarding Python. The more information, the better.


9.2 | Python Support
As stated above, the goal of this thread is to inspire people to get their feet wet with Python. You guys will run into errors and roadblocks. Post the errors here as reply. Let myself and the community help you on this thread. If you need assistance with a Python project that is not listed above, please post about it below for help. I will monitor this thread and help each and every person I can if they post their errors in here.






10.0 | Discord Bots / Discord.py
COMING SOON





11.0 | Closing Remarks
First off, I want to say thank you to anyone and everyone who took the time to read this thread in its entirety. It took me almost a week to get this thread how I wanted. I still consider it unfinished. There is still more I want to add and will add. I look forward to hearing feedback and thoughts from the community.

I hope this thread inspires someone in the community to learn more about python and programming in general. I hope this thread can stand as resource for all and act as a place of support for many.

Thank you all for your time.

- SiDev -
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