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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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📈 Аналитический обзор Telegram-канала Machine Learning with Python

Канал Machine Learning with Python (@codeprogrammer) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 68 475 подписчиков, занимая 2 403 место в категории Образование и 4 579 место в регионе Индия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 68 475 подписчиков.

Согласно последним данным от 03 ноября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -74, а за последние 24 часа — 12, при этом общий охват остаётся высоким.

  • Статус верификации: Не верифицирован
  • Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 4.07%. В первые 24 часа после публикации контент обычно набирает 1.55% реакций от общего числа подписчиков.
  • Охват публикаций: В среднем каждый пост получает 2 789 просмотров. В течение первых суток публикация набирает 1 062 просмотров.
  • Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 8.
  • Тематические интересы: Контент сосредоточен на ключевых темах, таких как insidead, learning, degree, evaluation, algorithm.

📝 Описание и контентная политика

Автор описывает ресурс как площадку для выражения субъективного мнения:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Благодаря высокой частоте обновлений (последние данные получены 04 ноября, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.

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This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Python53

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Git commands basics #MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligenc
Git commands basics #MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents http://t.me/codeprogrammer ✅

Python Network Programming Cheat Sheet 🖥 #MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization
Python Network Programming Cheat Sheet 🖥 #MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents http://t.me/codeprogrammer ✅

Regression & Classification Loss Functions #MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualizatio
Regression & Classification Loss Functions #MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents http://t.me/codeprogrammer ⭐️

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🐼 20 of the most used Pandas + PDF functions 👨🏻‍💻 The first time I used Pandas, I was supposed to quickly clean and organize a raw and complex dataset with the help of Pandas functions. Using the groupby function, I was able to categorize the data and get in-depth analysis of customer behavior. Best of all, it was when I used loc and iloc that I could easily filter the data. ✔️ Since then I decided to prepare a list of the most used Pandas functions that I use on a daily basis. Now this list is ready! In the following, I will introduce 20 of the best and most used Pandas functions: 🏳️‍🌈 read_csv(): Fast data upload from CSV files 🏳️‍🌈 head(): look at the first five rows of the database to start.. 🏳️‍🌈 info(): Checking data structure such as data type and empty values. 🏳️‍🌈 describe(): Generate descriptive statistics for numeric columns. 🏳️‍🌈 loc[ ]: accesses rows and columns by label or condition. 🏳️‍🌈 iloc[ ]: Access data by row number. 🏳️‍🌈 merge(): Merge dataframes with common columns. 🏳️‍🌈 groupby(): Grouping for easier analysis. 🏳️‍🌈 pivot_table(): Summarize data in pivot table format. 🏳️‍🌈 to_csv(): Save data as a CSV file. 🏳️‍🌈 pd.concat(): Concatenate multiple dataframes in rows or columns. 🏳️‍🌈 pd.melt(): Convert wide format data to long format. 🏳️‍🌈 pd.pivot_table(): Create a pivot table with multiple levels. 🏳️‍🌈 pd.cut(): Split the data into specific intervals. 🏳️‍🌈 pd.qcut(): Sort data by percentage. 🏳️‍🌈 pd.merge(): Merge data in database style for advanced linking. 🏳️‍🌈 DataFrame.apply(): Apply a custom function to the data. 🏳️‍🌈 DataFrame.groupby(): Analyze grouped data. 🏳️‍🌈 DataFrame.drop_duplicates(): Drop duplicate rows. 🏳️‍🌈 DataFrame.to_excel(): Save data directly to Excel file. ┌ 🐼 Pandas Functions └ 📄 PDF #MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents http://t.me/codeprogrammer ⭐️

Best LLMs Courses Link: https://www.mltut.com/best-large-language-models-courses/ #MachineLearning #DeepLearning #BigData #Da
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Master #DataAnalytics for real-world problems. I have curated a list of 40 Data Analytics Projects (solved & explained) that
Master #DataAnalytics for real-world problems. I have curated a list of 40 Data Analytics Projects (solved & explained) that will help you build analytics skills using #Python. Includes projects like: 1. Rainfall Trends in India Analysis 2. Netflix Content Strategy Analysis 3. Creating a Mutual Fund Plan 4. Stock Market Portfolio Optimization 5. Metro Operations Optimization 6. Analyzing the Impact of Carbon Emissions Find this list of projects here: https://thecleverprogrammer.com/2024/11/01/data-analytics-projects-with-python/ 📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #deeplearning #Projects http://t.me/codeprogrammer ⭐️

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📈How to make $15,000 in a month in 2024? Easy!!! Lisa is now the hippest trader who is showing crazy results in the market! She was able to make over $15,000 in the last month! ❗️ Right now she has started a marathon on her channel and is running it absolutely free. 💡 To participate in the marathon, you will need to : 1. Subscribe to the channel SIGNALS BY LISA TRADER 📈 2. Write in private messages : “Marathon” and start participating! 👉CLICK HERE👈

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▶️ The best project oriented videos 💻 To learn data science 👨🏻‍💻 The best way to learn data science is to combine theoretical learning with practical projects. After you have mastered the main concepts and tools, stop wasting your time and start learning project-based and doing real projects! ✅ Here I put 17 real data science projects in video form:👇 1️⃣ Making machine learning transparent with LINK ⬅️ AI 2️⃣ LINK practical guide ⬅️ PySpark 3️⃣ Construction of LINK model ⬅️ SRKGPT 4️⃣ Building a recovery system ⬅️ LINK 5️⃣ Strengthening small models ⬅️ (2) , (1) 6️⃣ Set Falon and Lama-2 ⬅️ (2) , (1) 7️⃣ Embedding data using LINK ⬅️ BERT 8️⃣ Compression of models ⬅️ LINK 9️⃣ Dynamic pricing in business ⬅️ LINK 1️⃣ Product embedding in big data ⬅️ LINK 1️⃣ Twitter recommender systems ⬅️ LINK 1️⃣ How the Twitter algorithm works ⬅️ LINK 1️⃣ Pinterest advertising systems ⬅️ LINK 1️⃣ Search for the nearest neighbor ⬅️ LINK 1️⃣ LINK controller ⬅️ PID 1️⃣ Training neural networks ⬅️ LINK ⚫️ Data dimensionality reduction with LINK ⬅️ PCA