This is a Python for data science, machine learning or Artificial Intelligence tutorial for beginners. In this tutorial you will have a solid understanding of the following basic Python topics:
Chapters:
0:00 Introduction to Python programming - Python basics
35:33 Data object types  and Type conversion
48:17 Operators and Expressions
1:14:15 Exception Handling
1:34:36 String Methods for Manipulating String Data
2:13:25 Functions
2:28:38 Function Scope
2:38:38 Function Arguments
2:47:54 Conditional Statements and Loops
3:14:41 Essential Built-in Modules
3:26:26 Develop a Simple Game Program

https://youtu.be/ISv6XIl1hn0

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Learn how to convert XML data to a Pandas DataFrame in Python with this easy-to-follow tutorial. Start optimizing your data analysis process today!
https://www.youtube.com/watch?v=y2KJJ6uH9tE

Harry up 😁 programmers is increasing linearly.



According to the #bardai search results, programmers are expected to be 30 million in 2024 in the world workforce.



This is amazing for newbies.



Data source: bardai

Visualization is done by @asibehtenager

#visualization #data

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What is the output of the above code? Comment your answer. Join #epythonlab Https://t.me/epythonlab

Object oriented Programming is an important concept that must be known by all computer coders. https://www.youtube.com/watch?v=I7z6i1QTdsw

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What is Pandas?

Pandas is an open source library, providing high-performance, easy-to-use data structures and data analysis tools for Python.

The DataFrame is one of Pandas' most important data structures. It's basically a way to store tabular data where you can label the rows and the columns. One way to build a DataFrame is from a dictionary and also importing from CSV(comma-separated value).

Here are the most common pandas functions for data analysis https://youtu.be/8a3Y-HT09sQ
#KeyNote #Pandas #DataFrame #DataScience

In Pandas, how do you select a single column from a DataFrame? Comment your answer ✅

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Creating and parsing XML documents in Python is a valuable skill for managing and exchanging structured data. In this tutorial, I'll cover the basics of creating XML documents and parsing them using Python's built-in XML module.

https://www.youtube.com/watch?v=WnbS90EzU0Y

If you are facing challenges of parsing and transforming nested XML document into a user friendly pandas DataFrame, this tutorial is for you. Please 🙏 Like, Share and comment any words you feel about this tutorial. Thanks for your support.

https://youtu.be/WQ-OhoXmHU8

Creating and parsing XML documents in Python is a valuable skill for managing and exchanging structured data. In this tutorial, I'll cover the basics of creating XML documents and parsing them using Python's built-in XML module.

https://www.youtube.com/watch?v=WnbS90EzU0Y

I'm curious🤭 about statistics Vs Probability
Here, I have made some tutorials about probability distribution for Machine learning using Scipy Python library https://www.youtube.com/playlist?list=PL0nX4ZoMtjYEl_1ONxAZHu65DPCQcsHmI

Mojo Programming Language - Full Course for Beginners
https://youtu.be/pyfCTxKcDPY

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By transforming our DataFrame into XML, we ensure that our data remains structured and readable across different platforms and applications.

Step by step guide: https://youtu.be/wNKKrt885xY

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Thanks for joining

In this topic modeling project-based tutorial, I have gone through the following steps:

1. Loads the documents(Generating sample documents)
2. Preprocesses the text by removing stop words and stemming words.
3. Creates a TF-IDF vector representation of the documents.
4. Performs LDA topic modeling with the specified number of topics.
5. Extracts the document-topic weight matrix.
6. Prepares the data for CSV format, including document IDs and topic weights.
7. Saves the results to the specified CSV file. https://youtu.be/uJCB2hRCB60

As a programmer, you must know the concept of object oriented programming. Here you go https://www.youtube.com/watch?v=I7z6i1QTdsw

Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok

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Machine Learning Project

Bag of words: A technique used to extract features from the text. It counts how many times a word appears in a document (corpus), and then transforms that information into a dataset.
https://youtu.be/tn-Tvi8CHmg

INTRODUCTION TO PROBABILITY DISTRIBUTION FOR MACHINE LEARNING WITH PYTHON

1. What is a random variable?
👉🏿 https://youtu.be/TkFipAuH-rY

2. Types of a random variable
👉🏿 https://youtu.be/jBYsKZOxR6k

3. Calculating probability using probability mass function
👉🏿 https://youtu.be/ceSvPxY_uAk

4. Calculating probability over a range
👉🏿 https://youtu.be/_WF9X4RyARA

5. Calculating Probability using the cumulative distribution function
👉🏿 https://youtu.be/tfoGiPlwiys

6. Calculating probability of continuous variable using density function and cumulative distribution function
   👉🏿 https://www.youtube.com/watch?v=ikete4WQaj0