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
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
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All Muslim Pythonista, Eid Mubarak
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Forwarded from Epython Lab
ai vs ml vs dl.pdf
470.3 KB
AI vs ML vs DL
Understanding Artificial Intelligence, Machine Learning, and Deep Learning
https://youtu.be/qSyDFGUXS9M
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Understanding Artificial Intelligence, Machine Learning, and Deep Learning
https://youtu.be/qSyDFGUXS9M
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This tutorial help you get started developing your own telegram bot from scratch https://youtu.be/y2y9eiD1-kM
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How to get started with Python programming from scratch - Beginners Guide https://www.youtube.com/watch?v=4IBGze0CYkk
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How to create xml documents using python https://www.youtube.com/watch?v=OtFqjpEEk_s&t=322s
YouTube
Creating XML Documents in Python
Hello everyone, and welcome to today's tutorial on creating XML documents in Python. I'm excited to guide you through this beginner's guide to generating XML structures programmatically using Python. Let's dive in!
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Forwarded from Epython Lab
Decorators in Python is used to ->
-> improve code readability
-> reduce code duplication
-> increase flexibility
Here you can learn how to implement decorators in Python step-by-step: https://www.youtube.com/watch?v=xpNt5qfgK38&list=PL0nX4ZoMtjYFwa6WIlGqs8g3EBTYt1k7y&index=8
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-> improve code readability
-> reduce code duplication
-> increase flexibility
Here you can learn how to implement decorators in Python step-by-step: https://www.youtube.com/watch?v=xpNt5qfgK38&list=PL0nX4ZoMtjYFwa6WIlGqs8g3EBTYt1k7y&index=8
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Learn #python with #epythonlab
YouTube
Decorators in Python Tutorial
Hello and welcome to @epythonlab . In this tutorial, you will learn about decorators in Python.
Decorators are a powerful and versatile tool in Python that allows you to modify the behavior of functions and classes without having to modify their source code.…
Decorators are a powerful and versatile tool in Python that allows you to modify the behavior of functions and classes without having to modify their source code.…
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Build your own Deep Learning Model with tensorflow and keras using Google Colab notebook https://www.youtube.com/watch?v=anyJVt5XzfE&list=PL0nX4ZoMtjYEhYVeSJkp2QhW658V0-R4e&index=3
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Forwarded from Epython Lab
Build your own Deep Learning Model with tensorflow and keras using Google Colab notebook https://www.youtube.com/watch?v=anyJVt5XzfE&list=PL0nX4ZoMtjYEhYVeSJkp2QhW658V0-R4e&index=3
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Project Idea: Building a spam classifier
Introduction
Spam detection is one of the major applications of Machine Learning in the interwebs today. Pretty much all of the major email service providers have spam detection systems built in and automatically classify such mail as 'Junk Mail'.
In this mission we will be using the Naive Bayes algorithm to create a model that can classify dataset SMS messages as spam or not spam, based on the training we give to the model. It is important to have some level of intuition as to what a spammy text message might look like.
What are spammy messages?
Usually they have words like 'free', 'win', 'winner', 'cash', 'prize', or similar words in them, as these texts are designed to catch your eye and tempt you to open them. Also, spam messages tend to have words written in all capitals and also tend to use a lot of exclamation marks. To the recipient, it is usually pretty straightforward to identify a spam text and our objective here is to train a model to do that for us!
Being able to identify spam messages is a binary classification problem as messages are classified as either 'Spam' or 'Not Spam' and nothing else. Also, this is a supervised learning problem, as we know what are trying to predict. We will be feeding a labelled dataset into the model, that it can learn from, to make future predictions. https://youtu.be/XdxaTc02FYA?si=XUFi1gsjRRmasRwj
Introduction
Spam detection is one of the major applications of Machine Learning in the interwebs today. Pretty much all of the major email service providers have spam detection systems built in and automatically classify such mail as 'Junk Mail'.
In this mission we will be using the Naive Bayes algorithm to create a model that can classify dataset SMS messages as spam or not spam, based on the training we give to the model. It is important to have some level of intuition as to what a spammy text message might look like.
What are spammy messages?
Usually they have words like 'free', 'win', 'winner', 'cash', 'prize', or similar words in them, as these texts are designed to catch your eye and tempt you to open them. Also, spam messages tend to have words written in all capitals and also tend to use a lot of exclamation marks. To the recipient, it is usually pretty straightforward to identify a spam text and our objective here is to train a model to do that for us!
Being able to identify spam messages is a binary classification problem as messages are classified as either 'Spam' or 'Not Spam' and nothing else. Also, this is a supervised learning problem, as we know what are trying to predict. We will be feeding a labelled dataset into the model, that it can learn from, to make future predictions. https://youtu.be/XdxaTc02FYA?si=XUFi1gsjRRmasRwj
YouTube
Spam Email Classifier Machine Learning Project
Learn how to use simple algorithms like Naive Bayes or Logistic Regression to build a model that can identify spam emails. In this tutorial, you will learn using a simple example of building a spam email classifier using Python, the scikit-learn library,…
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Forwarded from Epython Lab
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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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
Join #epythonlab https://news.1rj.ru/str/epythonlab
YouTube
Python Tutorial for Beginners: Python Full Course
🚀 Learn Python for Data Science, Machine Learning, and AI!
This full Python tutorial covers everything from Python basics to advanced topics like exception handling, string methods, loops, functions, and even building a simple game.
🔹 What You Will Learn:…
This full Python tutorial covers everything from Python basics to advanced topics like exception handling, string methods, loops, functions, and even building a simple game.
🔹 What You Will Learn:…
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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
https://www.youtube.com/watch?v=y2KJJ6uH9tE
YouTube
Convert XML to Pandas DataFrame in Python
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!
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Forwarded from Epython Lab
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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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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
Join https://news.1rj.ru/str/epythonlab/ for more resources
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What is the output of the above code? Comment your answer. Join #epythonlab Https://t.me/epythonlab
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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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YouTube
Introduction to Object Oriented Programming in Python
This is an introduction to object-oriented programming with Python. In this tutorial, we covered the following core concepts:
0:00 Objects
10:13:14 Classes
25:07:15 Inheritance
34:56:02 Project
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0:00 Objects
10:13:14 Classes
25:07:15 Inheritance
34:56:02 Project
-----------------------------------------------------------…
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
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
YouTube
Filtering Rows and Columns in Pandas DataFrame
Hi everyone, welcome to this tutorial on pandas data manipulation and aggregations functions. In this tutorial, you will learn about top pandas functions tha...
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In Pandas, how do you select a single column from a DataFrame? Comment your answer ✅
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