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 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist

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Tarmoq:Programming, data science, ML - free courses by Big Data Specialist Hindiston31 551 Texnologiyalar & Aralashmalar9 384...

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Data science/ML/AI (@datascience_bds) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 13 684 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 9 384-o'rinni va Hindiston mintaqasida 31 551-o'rinni egallagan.

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невідомо sanasidan buyon loyiha tez o‘sib, 13 684 obunachiga ega bo‘ldi.

11 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 150 ga, so‘nggi 24 soatda esa 11 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

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Jalb etish (ER): Auditoriya o‘rtacha 8.13% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.20% ini tashkil etuvchi reaksiyalarni to‘playdi.
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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 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatasci...”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 12 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

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+15030 kunlar

1 112

Post ko'rishlar

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~ 43548 soatlar

8.13%

Muloqot nisbati

~ 1

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Postlar arxiv

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When to Choose CatBoost Over XGBoost or LightGBM [Practical Guide] Boosting algorithms have become one of the most powerful algorithms for training on structural (tabular) data. I have been working with these 3 for years, even my bachelor thesis was comparison of these 3 algorithms alongside AdaBoost. This article explains when to use CatBoost over other ones. https://neptune.ai/blog/when-to-choose-catboost-over-xgboost-or-lightgbm ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

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Repost from Cool GitHub repositories

data-science This is a path for those of you who want to complete the Data Science undergraduate curriculum on your own time, for free, with courses from the best universities in the World. Creator: ossu Stars ⭐️: 14.5k Forked By: 2.6k GithubRepo:https://github.com/ossu/data-science ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @github_repositories_bds for more cool repositories. *This channel belongs to @bigdataspecialist group

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Knowledge Graphs Course Data Models, Knowledge Acquisition, Inference and Applications Department of Computer Science, Stanford University, Spring 2021 ⏳10 weeks, each week has slides and video lessons 📽 https://web.stanford.edu/class/cs520/ #datascience #machinelearning #tensorflow #scikitlearn #keras ➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @programming_books_bds for more

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ML_cheatsheets.pdf7.63 MB

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Another data science channel you might like: https://t.me/Artificial_Intelligence_DS

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Repost from Free programming books

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition by Aurélien Géron 📑 510 pages 🔗 Book link #datascience #machinelearning #tensorflow #scikitlearn #keras ➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @programming_books_bds for more

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The R Programming For Data Science A-Z Complete Diploma 2022 Rating ⭐️: 4.5 out of 5 Students 👨‍🎓: 38,584 Duration ⏰: 5h 6min 🔗 Course link

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ML Q&A.pdf2.14 KB

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Reproducible Data Science with Docker https://archive.org/details/pyconza2018-Reproducible_Data_Science_with_Docker

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Intro to Machine Learning by Kaggle Learn the core ideas in machine learning, and build your first models. 1 How Models Work The first step if you're new to machine learning. 2 Basic Data Exploration Load and understand your data. 3 Your First Machine Learning Model Building your first model. Hurray! #machinelearning #ml ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group 4 Model Validation Measure the performance of your model, so you can test and compare alternatives. 5 Underfitting and Overfitting Fine-tune your model for better performance. 6 Random Forests Using a more sophisticated machine learning algorithm. 7 Machine Learning Competitions Enter the world of machine learning competitions to keep improving and see your progress. 🔗 Course link

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Data Cleaning Guide.pdf2.11 MB

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FOUNDATIONS OF MACHINE LEARNING by Bloomberg Understand the Concepts, Techniques and Mathematical Frameworks Used by Experts in Machine Learning 🎬 30 video lessons with slides ⏰ 28 hours https://bloomberg.github.io/foml/#home #machinelearning #ml ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

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The Incredible PyTorch A curated list of tutorials, papers, projects, communities and more relating to PyTorch. https://www.ritchieng.com/the-incredible-pytorch/ #pytorch ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

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Lectures for UC Berkeley CS 182: Deep Learning Spring 2021 🎬 66 videos ⏰ 26 hours https://www.youtube.com/playlist?list=PL_iWQOsE6TfVmKkQHucjPAoRtIJYt8a5A ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

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cheatsheet-supervised-learning.pdf6.41 KB

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