Artificial Intelligence
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Ko'proq ko'rsatish
📈 Telegram kanali Artificial Intelligence analitikasi
Artificial Intelligence (@machinelearning_deeplearning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 56 625 obunachidan iborat bo'lib, Taʼlim toifasida 3 064-o'rinni va Hindiston mintaqasida 5 904-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 56 625 obunachiga ega bo‘ldi.
01 Noyabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 423 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 4.48% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.54% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 534 marta ko‘riladi; birinchi sutkada odatda 874 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 13 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent learning, classification, layer, pattern, chatbot kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“🔰 Machine Learning & Artificial Intelligence Free Resources
🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more
For Promotions: @love_data”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 02 Noyabr, 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.
56 625
Obunachilar
+1524 soatlar
+737 kun
+42330 kun
Postlar arxiv
56 625
Here are the top 5 machine learning projects that are suitable for freshers to work on:
1. Predicting House Prices: Build a machine learning model that predicts house prices based on features such as location, size, number of bedrooms, etc. This project will help you understand regression techniques and feature engineering.
2. Image Classification: Create a model that can classify images into different categories such as cats vs. dogs, fruits, or handwritten digits. This project will introduce you to convolutional neural networks (CNNs) and image processing.
3. Sentiment Analysis: Develop a sentiment analysis model that can classify text data as positive, negative, or neutral. This project will help you learn natural language processing techniques and text classification algorithms.
4. Credit Card Fraud Detection: Build a model that can detect fraudulent credit card transactions based on transaction data. This project will help you understand anomaly detection techniques and imbalanced classification problems.
5. Recommendation System: Create a recommendation system that suggests products or movies to users based on their preferences and behavior. This project will introduce you to collaborative filtering and recommendation algorithms.
These projects will not only enhance your machine learning skills but also provide you with practical experience in working on real-world data science problems.
56 625
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56 625
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56 625
Book: 📚Exercises in Machine Learning
Authors: Michael U. Gutmann
year: 2024
pages: 211
56 625
Want to build AI Apps and get jobs in GenAI domain? 🚀
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✅ Working on Audio Models
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56 625
🚓 Deep Learning Roadmap 2024- Step-by-Step Career Path
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