Epython Lab – Telegram
Epython Lab
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Welcome to Epython Lab, where you can get resources to learn, one-on-one trainings on machine learning, business analytics, and Python, and solutions for business problems.

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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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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
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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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What is the result of expression eval('2+3)*2 ?
Anonymous Quiz
44%
10
2%
7
54%
error
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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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What is the output of the above code? Comment your answer. Join #epythonlab Https://t.me/epythonlab
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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
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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
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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
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Forwarded from Epython Lab
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
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