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Coding Projects

Coding Projects

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Channel specialized for advanced concepts and projects to master: * Python programming * Web development * Java programming * Artificial Intelligence * Machine Learning Managed by: @love_data

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📈 Analytical overview of Telegram channel Coding Projects

Channel Coding Projects (@programming_experts) in the English language segment is an active participant. Currently, the community unites 67 947 subscribers, ranking 1 912 in the Technologies & Applications category and 4 646 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 67 947 subscribers.

According to the latest data from 06 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 21 over the last 30 days and by -10 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 3.37%. Within the first 24 hours after publication, content typically collects 1.01% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 291 views. Within the first day, a publication typically gains 686 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 4.
  • Thematic interests: Content is focused on key topics such as |--, algorithm, array, framework, javascript.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Channel specialized for advanced concepts and projects to master: * Python programming * Web development * Java programming * Artificial Intelligence * Machine Learning Managed by: @love_data”

Thanks to the high frequency of updates (latest data received on 07 November, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

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67 947
Subscribers
-1024 hours
+327 days
+2130 days
Posts Archive
+3
50 Projects In 50 Days - HTML, CSS & JavaScript.zip.001

+4
Machine_Learning_Project_6_Imdb_sentiment_review_Analysis_using.zip0.81 KB

"Here are the some Machine Learning Projects"

+3
NLP Projecct 1.ResumeScreening.zip7.62 KB

"Here are the some Natural Language Processing Projects"

+2
Library Management.zip0.42 KB

C language Projects ⬇️⬇️⬇️

Check out the list of top 10 Python projects on GitHub given below. 1. Magenta: Explore the artist inside you with this python project. A Google Brain’s brainchild, it leverages deep learning and reinforcement learning algorithms to create drawings, music, and other similar artistic products. 2. Photon: Designing web crawlers can be fun with the Photon project. It is a fast crawler designed for open-source intelligence tools. Photon project helps you perform data crawling functions, which include extracting data from URLs, e-mails, social media accounts, XML and pdf files, and Amazon buckets. 3. Mail Pile: Want to learn some encrypting tricks? This project on GitHub can help you learn to send and receive PGP encrypted electronic mails. Powered by Bayesian classifiers, it is capable of automatic tagging and handling huge volumes of email data, all organized in a clean web interface. 4. XS Strike: XS Strike helps you design a vulnerability to check your network’s security. It is a security suite developed to detect vulnerability attacks. XSS attacks inject malicious scripts into web pages. XSS’s features include four handwritten parsers, a payload generator, a fuzzing engine, and a fast crawler. 5. Google Images Download: It is a script that looks for keywords and phrases to optionally download the image files. All you need to do is, replicate the source code of this project to get a sense of how it works in practice. 6. Pandas Project: Pandas library is a collection of data structures that can be used for flexible data analysis and data manipulation. Compared to other libraries, its flexibility, intuitiveness, and automated data manipulation processes make it a better choice for data manipulation. 7. Xonsh: Used for designing interactive applications without the need for command-line interpreters like Unix. It is a Python-powered Shell language that commands promptly. An easily scriptable application that comes with a standard library, and various types of variables and has its own virtual environment management system. 8. Manim: The Mathematical Animation Engine, Manim, can create video explainers. Using Python 3.7, it produces animated videos, with added illustrations and display graphs. Its source code is freely available on GitHub and for tutorials and installation guides, you can refer to their 3Blue1Brown YouTube channel. 9. AI Basketball Analysis: It is an artificial intelligence application that analyses basketball shots using an object detection concept. All you need to do is upload the files or submit them as a post requests to the API. Then the OpenPose library carries out the calculations to generate the results. 10. Rebound: A great project to put Python to use in building Stackoverflow content, this tool is built on the Urwid console user interface, and solves compiler errors. Using this tool, you can learn how the Beautiful Soup package scrapes StackOverflow and how subprocesses work to find compiler errors.

Coding Projects in Python.pdf21.87 MB

11. Error Handling.zip333.22 MB

10. Modules In JavaScript.zip320.64 MB

9. Asynchronous JavaScript - Part 02.zip234.82 MB

9. Asynchronous JavaScript - Part 01.zip633.85 MB

8. OOP vs FP.zip242.29 MB

7. Functional Programming - Part 02.zip246.43 MB

7. Functional Programming - Part 01.zip635.93 MB

6. Object Oriented Programming - Part 02.zip369.16 MB

6. Object Oriented Programming - Part 01.zip594.08 MB

5_The_2_Pillars_Closures_and_Prototypal_Inheritance_Part_02.zip596.35 MB

5_The_2_Pillars_Closures_and_Prototypal_Inheritance_Part_01.zip672.17 MB