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Data science/ML/AI

Data science/ML/AI

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Data science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers πŸ‘‰ https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist

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πŸ“ˆ Telegram kanali Data science/ML/AI analitikasi

Data science/ML/AI (@datascience_bds) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 14 054 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 9 083-o'rinni va Hindiston mintaqasida 28 033-o'rinni egallagan.

πŸ“Š Auditoriya koβ€˜rsatkichlari va dinamika

Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ sanasidan buyon loyiha tez oβ€˜sib, 14 054 obunachiga ega boβ€˜ldi.

30 Oktabr, 2026 dagi oxirgi ma’lumotlarga koβ€˜ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 69 ga, soβ€˜nggi 24 soatda esa -2 ga oβ€˜zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya oβ€˜rtacha 9.83% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.11% ini tashkil etuvchi reaksiyalarni toβ€˜playdi.
  • Post qamrovi: Har bir post oβ€˜rtacha 1 382 marta koβ€˜riladi; birinchi sutkada odatda 297 ta koβ€˜rish yigβ€˜iladi.
  • Reaksiyalar va oβ€˜zaro ta’sir: Auditoriya faol: har bir postga oβ€˜rtacha 4 ta reaksiya keladi.
  • Tematik yoβ€˜nalishlar: Kontent panda, learning, row, api, ethic kabi asosiy mavzularga jamlangan.

πŸ“ Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
β€œData science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers πŸ‘‰ https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatasci...”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 31 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boβ€˜lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini koβ€˜rsatadi.

14 054
Obunachilar
-224 soatlar
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+6930 kun
Postlar arxiv
Different Probability Distributions used in Data Science
Different Probability Distributions used in Data Science

Python Data Science Handbook Python Data Science Handbook: full text in Jupyter Notebooks. This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks. Creator: Jake Vanderplas Stars⭐️: 39k Fork: 17.1K Repo: https://github.com/jakevdp/PythonDataScienceHandbook βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Deep Learning Methods (Classification)
Deep Learning Methods (Classification)

The essential data science venn diagram
The essential data science venn diagram

Data Science Projects - Data Analysis & Machine Learning Learn how to build Data Science Projects with Python. Classification, Time-Series and NLP Projects. Not for beginners. Rating ⭐️: 4.8 out 5 Students πŸ‘¨β€πŸŽ“ : 5,201 Duration ⏰ : 1hr 44min on-demand video Created by πŸ‘¨β€πŸ«: Onur BaltacΔ± πŸ”— Course Link #Projects #Data_Analysis #Machine_Learning #Data_Science βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– πŸ‘‰Join @bigdataspecialist for moreπŸ‘ˆ

Choosing a statistical test
Choosing a statistical test

Machine Learning & Data Science from Caltech This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML has become one of the hottest fields of study today, taken up by undergraduate and graduate students from more than 20 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects. ⏰ Free Online Course 🎬 18 Video lessons πŸ“ downloadable resources πŸƒβ€β™‚οΈ Self paced Offered by: Caltech πŸ”— Course link #Machine #Leaning #machinelearning #data_science βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– πŸ‘‰Join @bigdataspecialist for moreπŸ‘ˆ

Complete Data Science Roadmap 2023
Complete Data Science Roadmap 2023

Data Science job expectation vs reality
Data Science job expectation vs reality

Data Science for Beginners - A Curriculum Azure Cloud Advocates at Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data Science. Each lesson includes pre-lesson and post-lesson quizzes, written instructions to complete the lesson, a solution, and an assignment. Our project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'. Creator: Microsoft Stars⭐️: 21.6k Fork: 4.3K Repo: https://github.com/microsoft/Data-Science-For-Beginners βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Underfitting vs Overfitting
Underfitting vs Overfitting

15 Different Types of Data Scientists [with Responsibilities] A Data Scientist is a person who uses his/her skillset to gather, manage and store data for analysis. This is not easy as it sounds; a single person cannot do handling and engineer data. Proficiency in programming, mathematics, statistics, databases, etc., are some of the basic skills required to pursue different data science types of activities. Creating various types of data science models is the key responsibility of a data scientist. Financial models, Business models, and Machine learning models are some of the models which are developed by different types of data scientists. Data science is a broad term; the number of activities involved in data science is classified among professionals called Data Scientists. Let's explore the different types of data scientists along with their responsibilities. πŸ”— Article Link #Data_Science #Data #Science #datascience_types βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Data Science vs Data Analytics Skills
Data Science vs Data Analytics Skills

INTRODUCTION TO DATA SCIENCE/Machine Learning In this course, I include easy-to-understand materials covering topics from data mining and machine learning. I try to explain the algorithms and the mathematics behind those algorithms in such a way that the resources do not overwhelm the learners. At the same time, I make sure that each lecture has adequate core content to build a data science foundation. I am still creating content and adding them to this curriculum. πŸ†“ Free Online Course 🎬 video lessons πŸƒβ€β™‚οΈ Self paced Modules ⏰: 6 Source: computing4all πŸ”— Course Link #Data_Science #Data #Science βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Data Science and Machine Learning by Dirk P. Kroese, Zdravko I. Botev, Thomas Taimre, Radislav Vaisman πŸ“„ 533 pages πŸ”— Book Link #data_science #machinelearning βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– Join @datascience_bds for more

KNN Algorithm for Regression
KNN Algorithm for Regression

Basics of Pandas for Data Analysis & Data Science Learn Basics of Pandas for Data Analysis , Data Manipulation , Data Visualisation & Data Science Rating ⭐️: 4.6 out 5 Students πŸ‘¨β€πŸŽ“ : 2,376 Duration ⏰ : 1hr 55min on-demand video Created by πŸ‘¨β€πŸ«: Shan Singh πŸ”— Course Link #Pandas #Data_Analysis #Data_Visualization #Data_Science βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– πŸ‘‰Join @bigdataspecialist for moreπŸ‘ˆ

Data Scientist and Data Engineer
Data Scientist and Data Engineer

Repost from Python Learning
Netflix ML Architecture
Netflix ML Architecture

Finding your career path in Data
Finding your career path in Data