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Machinelearning

Machinelearning

Kanalga Telegram’da o‘tish

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

📈 Telegram kanali Machinelearning analitikasi

Machinelearning (@ai_machinelearning_big_data) Rus til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 292 329 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 328-o'rinni va Rossiya mintaqasida 1 292-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 292 329 obunachiga ega bo‘ldi.

09 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -6 200 ga, so‘nggi 24 soatda esa -193 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 7.33% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 5.53% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 21 439 marta ko‘riladi; birinchi sutkada odatda 16 173 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 154 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 10 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.

292 329
Obunachilar
-19324 soatlar
-1 2987 kunlar
-6 20030 kunlar
Postlar arxiv
How to train an algorithm to successfully pass the "Sonic The Hedgehog" game? Sergey Kolesnikov together with his team took the 4th place out of 900+ in the Open AI contest, and now is telling how to reach it. https://medium.com/swlh/at-the-speed-of-reinforcement-learning-an-openai-contest-story-6ed34fe7a3bb

Необычные материалы в робототехнике. У каждого робота должен быть блестящий металлический зад, это знают все. Но в реальных роботах металла не так уж и много — с ним соседствуют пластики, композиты и силикон, а порой и совсем нестандартные субстанции: http://amp.gs/hCG8

@robotics_channel — канал о робототехнике, искусственном разуме и сферах их применения. Регулярные новости, статьи, вакансии,
@robotics_channel — канал о робототехнике, искусственном разуме и сферах их применения. Регулярные новости, статьи, вакансии, обучающие курсы и полезные ресурсы.

Brilliant post on #CS and #Software about strategy and psychology of Software Development, which is highly applicable to Data Science too. “Imaginary Problems Are the Root of Bad Software” https://medium.com/s/story/imaginary-problems-d4f2921bd1b8

Two Sigma: Using News to Predict Stock Movements Use news analytics to predict stock price performance 1st place - $25,000 2nd place - $20,000 3rd place - $15,000 4th through 7th place - $10,000 each This is a two-stage competition consisting of a Submission period and a Scoring period. In the Submission period, entrants will train their models in Kaggle Kernels. During the Scoring period, models submitted at the end of the submission period will be evaluated against regularly updated news and market data. Start Date: 9/25/2018 Rules Acceptance/Team Merger Deadline: 1/2/2019 Submission Deadline: 1/8/2019 After this date, we will not be taking any more submissions. You can sit back and watch the leaderboard unfold. Remember to select your two best submissions to be rescored. In this competition we will not auto-select your two submissions. End Date: 7/15/2019 https://www.kaggle.com/c/two-sigma-financial-news

Geoffrey Hinton: The Foundations of Deep Learning https://www.youtube.com/watch?v=zl99IZvW7rE

How to Develop 1D Convolutional Neural Network Models for Human Activity Recognition https://machinelearningmastery.com/cnn-models-for-human-activity-recognition-time-series-classification/

deep learning object detection A paper list of object detection using deep learning. https://github.com/hoya012/deep_learning_object_detection

Machine Learning Crash Course with TensorFlow APIs https://developers.google.com/machine-learning/crash-course/

Machinelearning - Telegram kanali @ai_machinelearning_big_data statistikasi va tahlili