Github Top Repositories

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

📈 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 13 354 subscribers, ranking 15 230 in the Education category and 31 848 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 13 354 subscribers.

According to the latest data from 18 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 431 over the last 30 days and by 13 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 1.06%. Within the first 24 hours after publication, content typically collects 0.78% reactions from the total number of subscribers.
Post reach: On average, each post receives 142 views. Within the first day, a publication typically gains 104 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.

📝 Description and content policy

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

Thanks to the high frequency of updates (latest data received on 19 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.

13 354

Subscribers

+1324 hours

+757 days

+43130 days

142

Post views

~ 10424 hours

~ 11948 hours

1.06%

Engagement rate

~ 40

Posts per day

Ads index

beta

Posts Archive

13 355

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🔖 ImageBind: One Embedding Space To Bind Them All 📝 This project is a significant step forward in understanding and connecting information from diverse sources like images, text, audio, video, and even motion sensor data. ⚙️ Supports 6 Modalities: 📷 Image 📝 Text 🔈 Audi 🎥 Video 🦴 IMU sensor data (e.g., accelerometer) 🙄 Depth/Thermal & 3D data Interestingly, only some modalities had labels, yet ImageBind learned to align them through self-supervised learning. 💫 Key Features: ..No need for paired data (e.g., images and audio don’t have to be aligned)..Leverages contrastive learning for learning joint embedding space ..Competes with CLIP and AudioCLIP, but with better accuracy and coverage..Enables zero-shot retrieval (e.g., finding relevant video using just a sentence) 📌 Repo: https://github.com/facebookresearch/ImageBind 🔍 By: https://t.me/DataScienceN 🌟 #ImageBind #MultimodalAI #MetaAI #DeepLearning #SelfSupervised

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🔖 Project name : Analysis of Covid-19 chest x-rays 📝 In order to diagnose patients with Covid-19, the analysis of chest X-rays is a possibility to be explored to more easily detect positive cases. If the classification through deep learning of such data proves effective in detecting positive cases, then this method can be used in hospitals and clinics when traditional testing cannot be done. 📌 Repo: https://github.com/rehabaam/ds_covid19_project 🔍 By: https://t.me/DataScienceN 🌟

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📌 Project name: Cat/Dog/Fox Lightning 2024 By: https://t.me/DataScienceN 🌟

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📌 Project name: Cat/Dog/Fox Lightning 2024 📝 Language: #Python 🔗 Dataset Link: https://www.kaggle.com/datasets/snmahsa/animal-image-dataset-cats-dogs-and-foxes 🖋 Download the dataset offline: https://t.me/datasets1/668

13 355

Are u ready?

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13 355

We will start soon

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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/codeprogrammer

13 355

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13 355

Repost from AI & ML Papers

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13 355

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13 355

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (2023)

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13 355

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13 355

Repost from Data Science Books

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