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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Tarmoq:📈 Telegram kanali Machine Learning with Python analitikasi
Machine Learning with Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 68 505 obunachidan iborat bo'lib, Taʼlim toifasida 2 398-o'rinni va Hindiston mintaqasida 4 584-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 68 505 obunachiga ega bo‘ldi.
30 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 44 ga, so‘nggi 24 soatda esa -15 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 3.96% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.47% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 712 marta ko‘riladi; birinchi sutkada odatda 1 004 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 9 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent insidead, learning, degree, evaluation, algorithm kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 31 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
68 505
Obunachilar
-1524 soatlar
-1027 kun
+4430 kun
Postlar arxiv
🤖🧠 Concerto: How Joint 2D-3D Self-Supervised Learning Is Redefining Spatial Intelligence
🗓️ 09 Nov 2025
📚 AI News & Trends
The world of artificial intelligence is rapidly evolving and self-supervised learning has become a driving force behind breakthroughs in computer vision and 3D scene understanding. Traditional supervised learning relies heavily on labeled datasets which are expensive and time-consuming to produce. Self-supervised learning, on the other hand, extracts meaningful patterns without manual labels allowing models to ...
#SelfSupervisedLearning #ComputerVision #3DSceneUnderstanding #SpatialIntelligence #AIResearch #DeepLearning
🤖🧠 Pico-Banana-400K: The Breakthrough Dataset Advancing Text-Guided Image Editing
🗓️ 09 Nov 2025
📚 AI News & Trends
Text-guided image editing has rapidly evolved with powerful multimodal models capable of transforming images using simple natural-language instructions. These models can change object colors, modify lighting, add accessories, adjust backgrounds or even convert real photographs into artistic styles. However, the progress of research has been limited by one crucial bottleneck: the lack of large-scale, high-quality, ...
#TextGuidedEditing #MultimodalAI #ImageEditing #AIResearch #ComputerVision #DeepLearning
🤖🧠 PokeeResearch: Advancing Deep Research with AI and Web-Integrated Intelligence
🗓️ 09 Nov 2025
📚 AI News & Trends
In the modern information era, the ability to research fast, accurately and at scale has become a competitive advantage for businesses, researchers, analysts and developers. As online data expands exponentially, traditional search engines and manual research workflows are no longer sufficient to gather reliable insights efficiently. This need has fueled the rise of AI research ...
#AIResearch #DeepResearch #WebIntelligence #ArtificialIntelligence #ResearchAutomation #DataAnalysis
🤖🧠 DeepAgent: A New Era of General AI Reasoning and Scalable Tool-Use Intelligence
🗓️ 09 Nov 2025
📚 AI News & Trends
Artificial intelligence has rapidly progressed from simple assistants to advanced reasoning systems capable of complex problem-solving. As tasks demand more autonomy, adaptability and real-world interaction, the AI field has entered the era of intelligent agent systems. These agents are expected not just to answer questions, but to think, plan, search, act and interact across digital ...
#GeneralAI #ArtificialIntelligence #AIReasoning #IntelligentAgents #ScalableAI #ToolUseAI
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Repost from Machine Learning with Python
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