Machinelearning

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Погружаемся в машинное обучение и Data Science Показываем как запускать любые LLm на пальцах. По всем вопросам - @haarrp @itchannels_telegram -🔥best channels Реестр РКН: clck.ru/3Fmqri

Ko'proq ko'rsatish

Tarmoq:Machinelearning Rossiya1 291 Texnologiyalar & Aralashmalar328...

📈 Telegram kanali Machinelearning analitikasi

Machinelearning (@ai_machinelearning_big_data) Rus til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 292 747 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 328-o'rinni va Rossiya mintaqasida 1 291-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 292 747 obunachiga ega bo‘ldi.

07 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -6 317 ga, so‘nggi 24 soatda esa -209 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 7.45% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 5.46% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 21 817 marta ko‘riladi; birinchi sutkada odatda 15 977 ta ko‘rish yig‘iladi.
Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 160 ta reaksiya keladi.
Tematik yo‘nalishlar: Kontent openai, claude, api, gemini, контекст kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Погружаемся в машинное обучение и Data Science Показываем как запускать любые LLm на пальцах. По всем вопросам - @haarrp @itchannels_telegram -🔥best channels Реестр РКН: clck.ru/3Fmqri”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 08 Iyul, 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.

292 747

Obunachilar

-20924 soatlar

-1 3687 kunlar

-6 31730 kunlar

21 817

Post ko'rishlar

~ 15 97724 soatlar

~ 17 79548 soatlar

7.45%

Muloqot nisbati

~ 6

Kuniga postlar

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Postlar arxiv

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Debugging your tensorflow code right (without so many painful mistakes) https://towardsdatascience.com/debugging-your-tensorflow-code-right-without-so-many-painful-mistakes-b48bd9145d5c?source=collection_home---4------0---------------------

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How to Improve Performance With Transfer Learning for Deep Learning Neural Networks https://machinelearningmastery.com/how-to-improve-performance-with-transfer-learning-for-deep-learning-neural-networks/

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Intuitive Deep Learning Part 1a: Introduction to Neural Networks What is Deep Learning? A very gentle and intuitive introduction to Neural Networks and how they work! https://towardsdatascience.com/intuitive-deep-learning-part-1a-introduction-to-neural-networks-aaeb3a1500df

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The Best of AI: New Articles Published This Month (January 2019) 10 data articles handpicked by the Sicara team, just for you https://blog.sicara.com/01-2019-best-ai-new-articles-this-month-8e2113fbd17b

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How to build AutoML from scratch https://medium.com/@alxmamaev/how-to-build-automl-from-scratch-ce45a4b51e0f

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The Quick Python Book 2018

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Designing non-linear navigation for machine learning and topic modeling experiences https://uxdesign.cc/designing-non-linear-navigation-for-machine-learning-and-topic-modeling-experiences-4ee969875ebe

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MIT Deep Learning Basics: Introduction and Overview with TensorFlow https://medium.com/tensorflow/mit-deep-learning-basics-introduction-and-overview-with-tensorflow-355bcd26baf0?linkId=63206779

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Improving Evolutionary Strategies with Generative Neural Networks https://arxiv.org/abs/1901.11271

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Искусственные нейронные сети выращивают навигационные клетки как в мозге https://habr.com/ru/post/438526/

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Predicting Kickstarter Campaign Success with Gradient Boosted Decision Trees: A Machine Learning Classification Problem https://medium.com/@rileypredum/predicting-kickstarter-campaign-success-with-gradient-boosted-decision-trees-a-machine-learning-23077436c5f7

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Browse state-of-the-art 509 leaderboards • 963 tasks • 700 datasets • 8598 papers with code https://paperswithcode.com/sota

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Keras challenges the Avengers https://towardsdatascience.com/keras-challenges-the-avengers-541346acb804?source=collection_home---4------2---------------------

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Interactive Controls in Jupyter Notebooks How to use interactive IPython widgets to enhance data exploration and analysis https://towardsdatascience.com/interactive-controls-for-jupyter-notebooks-f5c94829aee6

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Machine Learning with TensorFlow

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How to build an image classifier with greater than 97% accuracy https://medium.freecodecamp.org/how-to-build-the-best-image-classifier-3c72010b3d55

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https://habr.com/ru/company/mailru/blog/437940/

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Lessons Learned from Kaggle’s Airbus Challenge https://medium.com/@YassineAlouini/lessons-learned-from-kaggles-airbus-challenge-252e25c5efac?source=topic_page---------19------------------1

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https://habr.com/ru/post/435884/

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Google Researchers Have a New Alternative to Traditional Neural Networks Say hello to the capsule network. https://www.technologyreview.com/the-download/609297/google-researchers-have-a-new-alternative-to-traditional-neural-networks/