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Github Top Repositories

Github Top Repositories

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Top GitHub repositories in one place πŸš€ Explore the best projects in programming, AI, data science, and more.

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πŸ“ˆ Analytical overview of Telegram channel Github Top Repositories

Channel Github Top Repositories (@githubre) in the English language segment is an active participant. Currently, the community unites 13 288 subscribers, ranking 15 339 in the Education category and 32 388 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 13 288 subscribers.

According to the latest data from 11 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 383 over the last 30 days and by 5 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 1.11%. Within the first 24 hours after publication, content typically collects 0.75% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 148 views. Within the first day, a publication typically gains 99 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 1.
  • Thematic interests: Content is focused on key topics such as repository, fork, programming, statistic, description.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œTop GitHub repositories in one place πŸš€ Explore the best projects in programming, AI, data science, and more.”

Thanks to the high frequency of updates (latest data received on 12 June, 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 Education category.

13 288
Subscribers
+524 hours
+837 days
+38330 days
Posts Archive
πŸ”₯ Trending Repository: skills πŸ“ Description: Skills Catalog for Codex πŸ”— Repository URL: https://github.com/openai/skills πŸ“– Readme: https://github.com/openai/skills#readme πŸ“Š Statistics: 🌟 Stars: 2.6K stars πŸ‘€ Watchers: 26 🍴 Forks: 166 forks πŸ’» Programming Languages: Python - Shell - JavaScript 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: review-prompts πŸ“ Description: AI review prompts πŸ”— Repository URL: https://github.com/masoncl/review-prompts πŸ“– Readme: https://github.com/masoncl/review-prompts#readme πŸ“Š Statistics: 🌟 Stars: 192 stars πŸ‘€ Watchers: 9 🍴 Forks: 29 forks πŸ’» Programming Languages: Python - Shell 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: rag-from-scratch πŸ“ Description: No description available πŸ”— Repository URL: https://github.com/langchain-ai/rag-from-scratch πŸ“– Readme: https://github.com/langchain-ai/rag-from-scratch#readme πŸ“Š Statistics: 🌟 Stars: 6.8K stars πŸ‘€ Watchers: 60 🍴 Forks: 1.8K forks πŸ’» Programming Languages: Jupyter Notebook 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: nanochat πŸ“ Description: The best ChatGPT that $100 can buy. πŸ”— Repository URL: https://github.com/karpathy/nanochat πŸ“– Readme: https://github.com/karpathy/nanochat#readme πŸ“Š Statistics: 🌟 Stars: 41.4K stars πŸ‘€ Watchers: 289 🍴 Forks: 5.4K forks πŸ’» Programming Languages: Python - Jupyter Notebook - HTML - Shell 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: qui πŸ“ Description: A fast, single-binary qBittorrent web UI: manage multiple instances, automate torrent workflows, and cross-seed across trackers. πŸ”— Repository URL: https://github.com/autobrr/qui 🌐 Website: https://getqui.com πŸ“– Readme: https://github.com/autobrr/qui#readme πŸ“Š Statistics: 🌟 Stars: 2.6K stars πŸ‘€ Watchers: 8 🍴 Forks: 74 forks πŸ’» Programming Languages: Go - TypeScript - CSS - Python - Makefile - HTML 🏷️ Related Topics:
#go #golang #qbittorrent #libtorrent #workflows #qbit #cross_seed #cross_seeding
================================== 🧠 By: https://t.me/DataScienceM

Top 100 Data Science Interview Questions βœ… Data Science Basics 1. What is data science and how is it different from data analytics? 2. What are the key steps in a data science lifecycle? 3. What types of problems does data science solve? 4. What skills does a data scientist need in real projects? 5. What is the difference between structured and unstructured data? 6. What is exploratory data analysis and why do you do it first? 7. What are common data sources in real companies? 8. What is feature engineering? 9. What is the difference between supervised and unsupervised learning? 10. What is bias in data and how does it affect models? Statistics and Probability 11. What is the difference between mean, median, and mode? 12. What is standard deviation and variance? 13. What is probability distribution? 14. What is normal distribution and where is it used? 15. What is skewness and kurtosis? 16. What is correlation vs causation? 17. What is hypothesis testing? 18. What are Type I and Type II errors? 19. What is p-value? 20. What is confidence interval? Data Cleaning and Preprocessing 21. How do you handle missing values? 22. How do you treat outliers? 23. What is data normalization and standardization? 24. When do you use Min-Max scaling vs Z-score? 25. How do you handle imbalanced datasets? 26. What is one-hot encoding? 27. What is label encoding? 28. How do you detect data leakage? 29. What is duplicate data and how do you handle it? 30. How do you validate data quality? Python for Data Science 31. Why is Python popular in data science? 32. Difference between list, tuple, set, and dictionary? 33. What is NumPy and why is it fast? 34. What is Pandas and where do you use it? 35. Difference between loc and iloc? 36. What are vectorized operations? 37. What is lambda function? 38. What is list comprehension? 39. How do you handle large datasets in Python? 40. What are common Python libraries used in data science? Data Visualization 41. Why is data visualization important? 42. Difference between bar chart and histogram? 43. When do you use box plots? 44. What does a scatter plot show? 45. What are common mistakes in data visualization? 46. Difference between Seaborn and Matplotlib? 47. What is a heatmap used for? 48. How do you visualize distributions? 49. What is dashboarding? 50. How do you choose the right chart? Machine Learning Basics 51. What is machine learning? 52. Difference between regression and classification? 53. What is overfitting and underfitting? 54. What is train-test split? 55. What is cross-validation? 56. What is bias-variance tradeoff? 57. What is feature selection? 58. What is model evaluation? 59. What is baseline model? 60. How do you choose a model? Supervised Learning 61. How does linear regression work? 62. Assumptions of linear regression? 63. What is logistic regression? 64. What is decision tree? 65. What is random forest? 66. What is KNN and when do you use it? 67. What is SVM? 68. How does Naive Bayes work? 69. What are ensemble methods? 70. How do you tune hyperparameters? Unsupervised Learning 71. What is clustering? 72. Difference between K-means and hierarchical clustering? 73. How do you choose value of K? 74. What is PCA? 75. Why is dimensionality reduction needed? 76. What is anomaly detection? 77. What is association rule mining? 78. What is DBSCAN? 79. What is cosine similarity? 80. Where is unsupervised learning used? Model Evaluation Metrics 81. What is accuracy and when is it misleading? 82. What is precision and recall? 83. What is F1 score? 84. What is ROC curve? 85. What is AUC? 86. Difference between confusion matrix metrics? 87. What is log loss? 88. What is RMSE? 89. What metric do you use for imbalanced data? 90. How do business metrics link to ML metrics?

πŸ”₯ Trending Repository: Stable-Video-Infinity πŸ“ Description: [ICLR 26] Stable Video Infinity: Infinite-Length Video Generation with Error Recycling πŸ”— Repository URL: https://github.com/vita-epfl/Stable-Video-Infinity 🌐 Website: https://stable-video-infinity.github.io/homepage/ πŸ“– Readme: https://github.com/vita-epfl/Stable-Video-Infinity#readme πŸ“Š Statistics: 🌟 Stars: 1.6K stars πŸ‘€ Watchers: 30 🍴 Forks: 128 forks πŸ’» Programming Languages: Python - Shell 🏷️ Related Topics:
#dance_generation #long_video_generation #audio_driven_talking_face #video_diffusion_transformers #end_to_end_filming
================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: prek πŸ“ Description: ⚑ Better `pre-commit`, re-engineered in Rust πŸ”— Repository URL: https://github.com/j178/prek 🌐 Website: https://prek.j178.dev/ πŸ“– Readme: https://github.com/j178/prek#readme πŸ“Š Statistics: 🌟 Stars: 4.1K stars πŸ‘€ Watchers: 13 🍴 Forks: 126 forks πŸ’» Programming Languages: Rust 🏷️ Related Topics:
#git #pre_commit #git_hooks
================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: CodexBar πŸ“ Description: Show usage stats for OpenAI Codex and Claude Code, without having to login. πŸ”— Repository URL: https://github.com/steipete/CodexBar 🌐 Website: https://codexbar.app πŸ“– Readme: https://github.com/steipete/CodexBar#readme πŸ“Š Statistics: 🌟 Stars: 3.6K stars πŸ‘€ Watchers: 14 🍴 Forks: 250 forks πŸ’» Programming Languages: Swift - Shell - JavaScript 🏷️ Related Topics:
#swift #ai #codex #claude_code
================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: vibetunnel πŸ“ Description: Turn any browser into your terminal & command your agents on the go. πŸ”— Repository URL: https://github.com/amantus-ai/vibetunnel 🌐 Website: https://vt.sh πŸ“– Readme: https://github.com/amantus-ai/vibetunnel#readme πŸ“Š Statistics: 🌟 Stars: 3.4K stars πŸ‘€ Watchers: 11 🍴 Forks: 223 forks πŸ’» Programming Languages: TypeScript - Swift - HTML - Shell - JavaScript - Zig 🏷️ Related Topics:
#terminal #remote #vibecoding
================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: calibre πŸ“ Description: The official source code repository for the calibre ebook manager πŸ”— Repository URL: https://github.com/kovidgoyal/calibre 🌐 Website: https://calibre-ebook.com πŸ“– Readme: https://github.com/kovidgoyal/calibre#readme πŸ“Š Statistics: 🌟 Stars: 23.5K stars πŸ‘€ Watchers: 385 🍴 Forks: 2.5K forks πŸ’» Programming Languages: Python - C - C++ - HTML - Shell - XSLT 🏷️ Related Topics:
#python #ebook #epub #kindle #ebook_manager #calibre #ebook_reader #ebooks #ebook_formats #epub_generation
================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: Maestro πŸ“ Description: Agent Orchestration Command Center πŸ”— Repository URL: https://github.com/pedramamini/Maestro 🌐 Website: https://RunMaestro.ai πŸ“– Readme: https://github.com/pedramamini/Maestro#readme πŸ“Š Statistics: 🌟 Stars: 802 stars πŸ‘€ Watchers: 10 🍴 Forks: 108 forks πŸ’» Programming Languages: TypeScript 🏷️ Related Topics:
#opencode #codex #ai_agents #generative_ai #claude_code
================================== 🧠 By: https://t.me/DataScienceM

Here: GitHub repository to learn AI Engineering. It contains some of the best free courses, articles, tutorials, and videos on the following topics: Mathematical foundation Basics of AI and #ML Deep Learning and specializations Generative #AI Large language models (#LLM) Guides on #promptengineering #RAG, #agents, and #MCP See here: https://github.com/ashishps1/learn-ai-engineering πŸ‘‰ @CODEPROGRAMMER

πŸ”₯ Trending Repository: cline πŸ“ Description: Autonomous coding agent right in your IDE, capable of creating/editing files, executing commands, using the browser, and more with your permission every step of the way. πŸ”— Repository URL: https://github.com/cline/cline 🌐 Website: https://marketplace.visualstudio.com/items?itemName=saoudrizwan.claude-dev πŸ“– Readme: https://github.com/cline/cline#readme πŸ“Š Statistics: 🌟 Stars: 57.3K stars πŸ‘€ Watchers: 266 🍴 Forks: 5.7K forks πŸ’» Programming Languages: TypeScript - Go - JavaScript - Python - Shell - CSS 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: flowsint πŸ“ Description: A modern platform for visual, flexible, and extensible graph-based investigations. For cybersecurity analysts and investigators. πŸ”— Repository URL: https://github.com/reconurge/flowsint 🌐 Website: https://flowsint.io πŸ“– Readme: https://github.com/reconurge/flowsint#readme πŸ“Š Statistics: 🌟 Stars: 2K stars πŸ‘€ Watchers: 25 🍴 Forks: 257 forks πŸ’» Programming Languages: TypeScript - Python - CSS - JavaScript - Makefile - Dockerfile 🏷️ Related Topics:
#python #osint #recon #investigation
================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: mermaid-ascii πŸ“ Description: Render Mermaid graphs inside your terminal πŸ”— Repository URL: https://github.com/AlexanderGrooff/mermaid-ascii 🌐 Website: https://mermaid-ascii.art/ πŸ“– Readme: https://github.com/AlexanderGrooff/mermaid-ascii#readme πŸ“Š Statistics: 🌟 Stars: 751 stars πŸ‘€ Watchers: 3 🍴 Forks: 35 forks πŸ’» Programming Languages: Go - CSS - JavaScript - Shell - Makefile - Nix - Dockerfile 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: termux-app πŸ“ Description: Termux - a terminal emulator application for Android OS extendible by variety of packages. πŸ”— Repository URL: https://github.com/termux/termux-app 🌐 Website: https://f-droid.org/en/packages/com.termux πŸ“– Readme: https://github.com/termux/termux-app#readme πŸ“Š Statistics: 🌟 Stars: 49.4K stars πŸ‘€ Watchers: 1.4k 🍴 Forks: 5.9K forks πŸ’» Programming Languages: Java - C++ 🏷️ Related Topics:
#android #linux #terminal #termux #hacktoberfest
================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: claude-plugins-official πŸ“ Description: Official, Anthropic-managed directory of high quality Claude Code Plugins. πŸ”— Repository URL: https://github.com/anthropics/claude-plugins-official 🌐 Website: https://code.claude.com/docs/en/plugins πŸ“– Readme: https://github.com/anthropics/claude-plugins-official#readme πŸ“Š Statistics: 🌟 Stars: 5.7K stars πŸ‘€ Watchers: 59 🍴 Forks: 570 forks πŸ’» Programming Languages: Shell - Python 🏷️ Related Topics:
#skills #mcp #claude_code
================================== 🧠 By: https://t.me/DataScienceM

πŸ”₯ Trending Repository: 99 πŸ“ Description: Neovim AI agent done right πŸ”— Repository URL: https://github.com/ThePrimeagen/99 πŸ“– Readme: https://github.com/ThePrimeagen/99#readme πŸ“Š Statistics: 🌟 Stars: 1.9K stars πŸ‘€ Watchers: 26 🍴 Forks: 91 forks πŸ’» Programming Languages: Lua - Tree-sitter Query - Vim Script 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

LandingAI released a free course on Document AI. It teaches how to build document processing pipelines that extract text, tab
LandingAI released a free course on Document AI. It teaches how to build document processing pipelines that extract text, tables, charts, and forms without losing the context of the markup. The problem with classic OCR is that it "extracts letters", but breaks the meaning: - tables lose their structure (including merged cells) - the connections "chart β¬…οΈβž‘οΈ signature" fall apart - the reading order in multi-column becomes a mess The course shows how to build an agent-workflow that reads documents closer to how a human does it, through Agentic Document Extraction (ADE). What's inside: - why regular OCR fails on complex documents - how layout detection + correct reading order preserve the structure - how to parse PDF into Markdown/JSON and not lose the layout - how to collect RAG with ADE and vector databases - how to deploy event-driven document pipelines on AWS 3 hours, 6 practical code examples. Completely free. https://www.deeplearning.ai/short-courses/document-ai-from-ocr-to-agentic-doc-extraction/ πŸ‘‰ @DataScienceN