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Machine Learning & Artificial Intelligence | Data Science Free Courses
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Perfect channel to learn Data Analytics, Data Sciene, Machine Learning & Artificial Intelligence Admin: @coderfun
Ko'proq ko'rsatish📈 Telegram kanali Machine Learning & Artificial Intelligence | Data Science Free Courses analitikasi
Machine Learning & Artificial Intelligence | Data Science Free Courses (@datasciencefree) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 66 672 obunachidan iborat bo'lib, Taʼlim toifasida 2 475-o'rinni va Malayziya mintaqasida 435-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 66 672 obunachiga ega bo‘ldi.
18 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 676 ga, so‘nggi 24 soatda esa 20 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 1.12% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.51% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 750 marta ko‘riladi; birinchi sutkada odatda 1 007 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 5 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent sellerflash, waybienad, pricing, buybox, buyer kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Perfect channel to learn Data Analytics, Data Sciene, Machine Learning & Artificial Intelligence
Admin: @coderfun”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 19 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.
66 672
Obunachilar
+2024 soatlar
+1517 kunlar
+67630 kunlar
Postlar arxiv
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✅ If Data Science Tools Were Characters… 🧠🔍
📝 Excel — The Office Guy
Knows a bit of everything. Not flashy, but still gets the job done (until it crashes at 1M rows). 🤦♂️
🐍 Python — The All-Rounder
Writes poetry, builds models, scrapes web, visualizes data… and still has time for coffee. ☕
📊 Tableau — The Artist
Can turn boring data into jaw-dropping dashboards. Looks good, speaks in visuals. 🎨
🧮 R — The Statistician
Loves hypothesis tests and plots. Bit quirky, but unmatched in analysis. 🤓
🏗 SQL — The Architect
Knows where everything is stored. Can fetch exactly what you need… if you ask just right. 🏛️
🎯 Scikit-learn — The Model Trainer
Logistic, decision trees, clustering—you name it. Works fast, plays well with Python. ⚙️
🧠 TensorFlow/PyTorch — The Gym Bro
Lifts heavy deep learning weights. Complex but powerful. Needs proper tuning and GPUs. 💪
🗃 Pandas — The Organizer
Cleans, filters, groups, reshapes—loves playing with tables. But can be moody with large files. 🗂️
📍 Matplotlib/Seaborn — The Designer Duo
One is technical, the other stylish. Together they make your data look beautiful. ✨
🔁 Jupyter Notebook — The Presenter
Explains everything step by step. Talks code, visuals, and markdown—all in one flow. 🧑🏫
#DataScience #MachineLearning
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ChatGPT Prompt Cheat Sheet
An incredibly short book, but with a deep analysis of the internal mechanisms of Python, which we use every day. ❤️
Each chapter contains an explanation of a specific language feature, such as working with *args/**kwargs, mutable arguments, generators, decorators, context managers, enumerate/zip, exceptions, dunder methods, and other clever constructs.
Link: https://book.pythontips.com/en/latest/
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