Epython Lab

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

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 Join #epythonlab https://t.me/epythonlab

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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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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 Join #epythonlab https://t.me/epythonlab

Looking for a Remote Job? 💻🌍 🐍 Python ➡️ https://t.me/remote_python_jobs 🔮 AI/ML/DS  ➡️ https://t.me/remote_ai_jobs ☕️Java ➡️ https://t.me/remote_java_jobs 🐘 PHP ➡️ https://t.me/remote_php_jobs ♦️ Ruby ➡️ https://t.me/remote_ruby_job 🧑‍💻GO Lang ➡️ https://t.me/remote_go_jobs 🚀 DevOPS ➡️ https://t.me/remote_devops_jobs 💼 FrondEnd  ➡️ https://t.me/remote_frontend_jobs 📱Mobile ➡️ https://t.me/remote_mobile_jobs 🐞 QA ➡️ https://t.me/remote_qa_jobs Subscribe now and turn your skills into a thriving remote career! 💻🌍

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 Join #epythonlab https://t.me/epythonlab

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 👉Join Telegram https://t.me/epythonlab/ Learn #python with #epythonlab

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How to create xml documents using python https://www.youtube.com/watch?v=OtFqjpEEk_s&t=322s

Top AI Project Ideas for beginners

How to get started with Python programming from scratch - Beginners Guide How to learn Python from scratch https://www.youtube.com/watch?v=4IBGze0CYkk Join #epythonlab https://t.me/epythonlab

This tutorial help you get started developing your own telegram bot from scratch https://youtu.be/y2y9eiD1-kM Subscribe, share, like and join membership

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