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Data Science & Machine Learning

Data Science & Machine Learning

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Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data

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📈 Telegram kanali Data Science & Machine Learning analitikasi

Data Science & Machine Learning (@datasciencefun) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 75 833 obunachidan iborat bo'lib, Taʼlim toifasida 2 106-o'rinni va Hindiston mintaqasida 4 234-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 75 833 obunachiga ega bo‘ldi.

21 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 770 ga, so‘nggi 24 soatda esa 8 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 3.15% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.09% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 2 385 marta ko‘riladi; birinchi sutkada odatda 827 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 3 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent learning, accuracy, distribution, panda, dataset kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data

Yuqori yangilanish chastotasi (oxirgi ma’lumot 22 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.

75 833
Obunachilar
+824 soatlar
+717 kunlar
+77030 kunlar
Postlar arxiv
Data Science and Python

Adversarial Robustness for Machine Learning Pin-Yu Chen, 2022

Probabilistic Machine Learning for Finance and Investing Deepak Kanungo, 2022

Python_pandas_Cheat_Sheet.pdf5.49 KB

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ML Cheatsheets.pdf7.62 MB

Data Quality Fundamentals Barr Moses, 2022

American Express is hiring Position: Data Science Analyst 👉 Apply: https://aexp.eightfold.ai/careers/job/13347327 👍 All the best.

Hello Guys! This Platform Having Almost all Coding Courses For free! ‼️ Get Data scientists and Full stack development courses ❤ Sign up & Grab it 👇 https://bit.ly/3xgAzAT

'The Ultimate Guide to Machine Learning Job Interviews '

+1
Python for Data Science for Dummies John Paul Mueller, 2019

Pandas CheatSheet

Which of the following command isn't used in pandas?
Anonymous voting

Harvard CS109A #DataScience course materials — huge collection free & open! 1. Lecture notes 2. R code, #Python notebooks 3. Lab material 4. Advanced sections and more ... https://harvard-iacs.github.io/2019-CS109A/pages/materials.html

Machine learning Cookbook with python Rehan Guha, 2021

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Time Series Forecasting using Deep Learning Ivan Gridin, 2022

+1
Practical Computer Vision Applications Using Deep Learning with CNNs Ahmed Fawzy Gad, 2019

NVIDIA GTC is the most important conference for the era of AI and the metaverse. Join us online as we explore the innovations
NVIDIA GTC is the most important conference for the era of AI and the metaverse. Join us online as we explore the innovations that will impact your life’s work with the power of AI, computer graphics, data science, and more. The conference will run from September 19 -22, it is fully virtual and free to attend. Let innovation inspire your next idea, or solve your biggest challenge. With talks delivered by pioneers in their fields to relatable use cases and Deep Learning Institue training where you can gain NVIDIA certification, to Watch Parties where you can engage with your peers, you can be part of what comes next at GTC. Register today

Artificial Intelligence and Machine Learning for EDGE Computing Rajiv Pandey, 2022