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Coding Projects

Coding Projects

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📈 Analytical overview of Telegram channel Coding Projects

Channel Coding Projects (@coding_projects) in the English language segment is an active participant. Currently, the community unites 14 722 subscribers, ranking 8 703 in the Technologies & Applications category and 28 346 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 14 722 subscribers.

According to the latest data from 06 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -103 over the last 30 days and by 0 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 0%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 0 views. Within the first day, a publication typically gains 0 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
Find projects for almost all Programming Languages for free ! 🧑‍💻

Thanks to the high frequency of updates (latest data received on 07 July, 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.

14 722
Subscribers
No data24 hours
-247 days
-10330 days

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Incoming and Outgoing Mentions
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Attracting Subscribers
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December '24
+1 372
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+561
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January '23
+407
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December '22
+4 903
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Date
Subscriber Growth
Mentions
Channels
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Channel Posts
Get this ₹999 Workshop for FREE! 🔥🔥 🚀 Want to learn the exact skills Full Stack Developers will need in 2026? 💡 You’ll learn: ✅ Future-ready Full Stack skills ✅ AI is used in websites & apps ✅ Secure coding & real-world APIs ✅ What companies actually expect ⏳ Only for first 1000 registrations₹999 Workshop — FREE! 👉 Register Now : https://link.guvi.in/Curious_coder02736

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Python Notes By Yadnyesh!.pdf
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Sometimes reality outpaces expectations in the most unexpected ways. While global AI development seems increasingly fragmented, Sber just released Europe's largest open-source AI collection—full weights, code, and commercial rights included. ✅ No API paywalls. ✅ No usage restrictions. ✅ Just four complete model families ready to run in your private infrastructure, fine-tuned on your data, serving your specific needs. What makes this release remarkable isn't merely the technical prowess, but the quiet confidence behind sharing it openly when others are building walls. Find out more in the article from the developers. GigaChat Ultra Preview: 702B-parameter MoE model (36B active per token) with 128K context window. Trained from scratch, it outperforms DeepSeek V3.1 on specialized benchmarks while maintaining faster inference than previous flagships. Enterprise-ready with offline fine-tuning for secure environments. GitHub | HuggingFace | GitVerse GigaChat Lightning offers the opposite balance: compact yet powerful MoE architecture running on your laptop. It competes with Qwen3-4B in quality, matches the speed of Qwen3-1.7B, yet is significantly smarter and larger in parameter count. Lightning holds its own against the best open-source models in its class, outperforms comparable models on different tasks, and delivers ultra-fast inference—making it ideal for scenarios where Ultra would be overkill and speed is critical. Plus, it features stable expert routing and a welcome bonus: 256K context support. GitHub | Hugging Face | GitVerse Kandinsky 5.0 brings a significant step forward in open generative models. The flagship Video Pro matches Veo 3 in visual quality and outperforms Wan 2.2-A14B, while Video Lite and Image Lite offer fast, lightweight alternatives for real-time use cases. The suite is powered by K-VAE 1.0, a high-efficiency open-source visual encoder that enables strong compression and serves as a solid base for training generative models. This stack balances performance, scalability, and practicality—whether you're building video pipelines or experimenting with multimodal generation. GitHub | GitVerse | Hugging Face | Technical report Audio gets its upgrade too: GigaAM-v3 delivers speech recognition model with 50% lower WER than Whisper-large-v3, trained on 700k hours of audio with punctuation/normalization for spontaneous speech. GitHub | HuggingFace | GitVerse Every model can be deployed on-premises, fine-tuned on your data, and used commercially. It's not just about catching up – it's about building sovereign AI infrastructure that belongs to everyone who needs it.
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15 LPA Job Offer - With AI Certification 💻 IIT Patna has launched its latest batch to help you kickstart a career in AI & ML 💰15 LPA job offer as a fresher ⏰ Learn AI & Ml from IIT Patna ✅ Students & Fresher can apply Link: https://tinyurl.com/IIT-patna-Ai-Ml Need only serious candidates & Capable candidates required! So to apply have to pay Rs. 99/- The amount will be fully *refunded* once you attend the test. Big Opportunity, Do join asap! 💯
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3 054
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2 887
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2 956
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3 577
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2 996
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3 438
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