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AI and Machine Learning
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Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses
Ko'proq ko'rsatish📈 Telegram kanali AI and Machine Learning analitikasi
AI and Machine Learning (@machine_learning_courses) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 94 001 obunachidan iborat bo'lib, Taʼlim toifasida 1 568-o'rinni va Hindiston mintaqasida 3 028-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 94 001 obunachiga ega bo‘ldi.
23 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 993 ga, so‘nggi 24 soatda esa 92 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 7.92% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.62% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 7 435 marta ko‘riladi; birinchi sutkada odatda 1 526 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 learning, llm, linkedin, linux, udemy kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more!
Buy ads: https://telega.io/c/machine_learning_courses”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 24 Iyun, 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.
94 001
Obunachilar
+9224 soatlar
+1097 kunlar
+99330 kunlar
Postlar arxiv
94 001
🚀 TrajectoryCrafter (Moving-Camera Diffusion) is a new tool from Tencent that offers a new approach to redirecting camera trajectories in monochrome videos.
How the model works:
🌟 Initialization :
starts with an existing camera trajectory or even pure noise. This sets the initial state that the model will gradually improve.
The model uses two types of input data simultaneously: rendered point clouds (3D representations of scenes) and source videos.
🌟 Diffusion process:
The model learns to “clean up” random noise step by step, turning it into a sequence of trajectories. At each step, iterative refinement occurs — the model predicts what a more realistic trajectory should look like, based on given conditions (e.g., smoothness of motion, and consistency of the scene).
Instead of using only videos taken from different angles, the authors created a training set by combining extensive monocular videos (with a regular camera) with limited but high-quality multi-view videos. This strategy is achieved using what is called “double reprojection”, which helps the model better adapt to different scenes.
🌟 Generating the final trajectory:
After a series of iterations, when the noise is removed, a new camera trajectory is generated that meets the given conditions and has high quality visual dynamics.
Installation :
git clone --recursive https://github.com/TrajectoryCrafter/TrajectoryCrafter.git
cd TrajectoryCrafter
🖥 Github
🟡 Article
🟡 Project
🟡 Demo
🟡 Video94 001
🔅 AI Projects with Python, TensorFlow, and NLTK
📝 Supercharge your technical know-how and start building AI projects using Python, TensorFlow, and NLTK.
🌐 Author: Dhhyey Desai
🔰 Level: Intermediate
⏰ Duration: 24m
📋 Topics: TensorFlow, Artificial Intelligence, NLTK
🔗 Join Artificial intelligence for more courses
94 001
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📱Artificial intelligence
📱Advanced LLMs with Retrieval Augmented Generation (RAG): Practical Projects for AI Applications
94 001
🔅 Advanced LLMs with Retrieval Augmented Generation (RAG): Practical Projects for AI Applications
📝 Discover the core concepts of successful AI applications using LLMs to achieve high levels of performance and accuracy.
🌐 Author: Guy Ernest
🔰 Level: Advanced
⏰ Duration: 1h 47m
📋 Topics: Retrieval-Augmented Generation, Large Language Models, Artificial Intelligence
🔗 Join Artificial intelligence for more courses
94 001
💡 9 AI Skills to Master in 2026
It’s the infrastructure behind how smart businesses run today.
The gap between users and experts is closing fast.
But the gap between curiosity and capability is getting wider.
The difference comes down to skill, not just tools.
These are the nine that matter most in 2026.
Each one compounds the rest and turns AI from novelty into leverage.
1⃣ Prompt Engineering to ask better questions and get sharper answers
🔢 AI Workflow Automation to connect apps and remove repetitive work
🔢 AI Agents to build systems that act without human input
🔢 Retrieval-Augmented Generation (RAG) to give models access to your own data
🔢 Fine-Tuning and Custom GPTs to train models for your goals and tone
🔢 Multimodal AI to mix text, image, and audio in one workflow
🔢 AI Video Generation to turn ideas into content without editing tools
🔢 AI Tool Stacking to link platforms into a single automated system
🔢 LLM Evaluation and Management to measure accuracy, cost, and performance
94 001
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221k| 🔰 Linkedin Learning
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118k| 🔰 Python 3
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-◦-◦--◦-
068k| 🔰 Artificial Intelligence
068k| 🔰 Data Analysis and Databases
064k| 🔰 React and NextJs
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061k| 🔰 Linux and DevOps
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047k| 🔰 Business and Finance
045k| 🔰 Best Telegram Channels
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040k| 🔰 Mobile Apps
035k| 🔰 Linkedin Learning Courses
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035k| 🔰 Codedamn Courses
034k| 🔰 React 101
031k| 🔰 Crypto Tutorials
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030k| 🔰 Coding Interview
025k| 🔰 Telegram's Shorts
022k| 🔰 Linux Training
-◦-◦--◦-
022k| 🔰 The Coding Space
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🔰 2hrs on top & 8hrs in channel!
94 001
🔅 Natural Language Processing (NLP) on Amazon Bedrock
📝 This course addresses natural language AI tasks using Bedrock's LLMs, Amazon Q capabilities, and SageMaker NLP models.
🌐 Author: Noah Gift
🔰 Level: Intermediate
⏰ Duration: 56m
📋 Topics: Amazon Bedrock, Large Language Models, Natural Language Processing
🔗 Join Artificial intelligence for more courses
94 001
💡 The AI Universe
This visual guide clearly illustrates the different layers and concepts within Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI.
94 001
+1
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94 001
🔅 Everyday AI Concepts
📝 Learn key artificial intelligence concepts and discover how AI can benefit your team, organization, products, and services.
🌐 Author: Doug Rose
🔰 Level: General
⏰ Duration: 49m
📋 Topics: Artificial Intelligence for Business
🔗 Join Artificial intelligence for more courses
