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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 75 933 obunachidan iborat bo'lib, Taʼlim toifasida 2 103-o'rinni va Hindiston mintaqasida 4 204-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 75 933 obunachiga ega bo‘ldi.

23 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 731 ga, so‘nggi 24 soatda esa 33 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 2.95% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.86% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 2 239 marta ko‘riladi; birinchi sutkada odatda 650 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 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.

75 933
Obunachilar
+3324 soatlar
+587 kunlar
+73130 kunlar
Postlar arxiv
Udacity(udacity.com) courses collections Udacity's Android Basics Nanodegree Download Link- https://mega.nz/folder/nDgXkaob#5LPk0Hpz4HgZ7njcvyNmqw @datasciencefun Udacity's Machine Learning Engineer Nanodegree Download Link- https://mega.nz/folder/qX5BWKDD#s6JadsuGzsyELin6zYfU8Q @datasciencefun Udacity's Blockchain Nanodegree Download Link- https://mega.nz/folder/HD43EKTL#jcAo2OvAjEQmi0SqHELuyA Udacity's Data Analyst Nanodegree Download Link- https://mega.nz/folder/GbgnkCaR#gQodlI6pEkoKGIaqDhuCUg

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🔰Python Cheat Sheet for all Programmers🔰 Top 15 Cheat Sheets for Machine Learning, Data Science & Big Data 🖇Link : https://anonfiles.com/zcLcO0G5oc/Python_Top_15_Cheat_Sheets_for_Machine_Learning_Data_Science_Big_Data_rar Share and support us

Which of the following is an important library or framework for data visualization using PYTHON? [Not Machine learning]
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Data science Tools
Data science Tools

Building the Machine Learning Model
Building the Machine Learning Model

Which step is done just after collecting data?
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Do you want more books recommendations?
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Hello guys, if you are a beginner in data science and want to learn it from scratch. Then, there is a good news for you. Currently Amazon is providing 77% off on this data science book Highly recommend if you are beginner in data science Purchase it before the price increases https://bit.ly/30j72GI Flipkart is selling the same book for rs. 2500 https://bit.ly/39K2pIJ Enjoy learning 👍

👩🏻‍💻 Why should one study Linear Algebra for ML? 👉🏼 Clearly, to develop a better intuition for machine learning and deep learning algorithms and not treat them as black boxes. This would allow you to choose proper hyper-parameters and develop a better model. You would also be able to code algorithms from scratch and make your own variations to them as well. 👉🏼 Learn Linear Algebra for Machine Learning with: Khan Academy: https://www.khanacademy.org/math/linear-algebra Udacity: https://www.udacity.com/course/linear-algebra-refresher-course--ud953 Coursera: https://www.coursera.org/learn/linear-algebra-machine-learning Here are some amazing freely available ebooks on the same topic: Mathematics for Machine Learning: https://mml-book.github.io/book/mml-book.pdf An Introduction to Statistical Learning: https://faculty.marshall.usc.edu/gareth-james/ISL/ Happy machine learning! 🎉

Pingzee Technologies Pvt. Ltd. is hiring Data Science interns on Dockship. Pingzee provides a cloud-based infrastructure to simplify the real-time data engineering to help in building fast, secure and highly scalable real-time solutions. Participate in Sales Forecasting and EDA Challenge and get a chance to be interviewed for this position. Only limited slots are available. Apply Now: https://bit.ly/309rREi