uz
Feedback
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 292 519 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 328-o'rinni va Rossiya mintaqasida 1 290-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 292 519 obunachiga ega bo‘ldi.

08 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -6 274 ga, so‘nggi 24 soatda esa -221 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 7.46% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 5.47% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 21 812 marta ko‘riladi; birinchi sutkada odatda 16 003 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 159 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 09 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.

292 519
Obunachilar
-22124 soatlar
-1 3547 kunlar
-6 27430 kunlar
Postlar arxiv
How to Create a Random-Split, Cross-Validation, and Bagging Ensemble for Deep Learning in Keras https://machinelearningmastery.com/how-to-create-a-random-split-cross-validation-and-bagging-ensemble-for-deep-learning-in-keras/

30 Data Science Punchlines A holiday reading list condensed into 30 quotes https://towardsdatascience.com/data-science-conversation-starters-84affd2347f6

10 Exciting Ideas of 2018 in NLP http://ruder.io/10-exciting-ideas-of-2018-in-nlp/

Best NLP articles explanation https://jalammar.github.io/illustrated-bert/

Facebook has released #PyText — new framework on top of #PyTorch. This framework is build to make it easier for developers to build #NLP models. https://code.fb.com/ai-research/pytext-open-source-nl.. Github: https://github.com/facebookresearch/pytext

How to Stop Training Deep Neural Networks At the Right Time Using Early Stopping https://machinelearningmastery.com/how-to-stop-training-deep-neural-networks-at-the-right-time-using-early-stopping/

A Gentle Introduction to Early Stopping to Avoid Overtraining Deep Learning Neural Network Models https://machinelearningmastery.com/early-stopping-to-avoid-overtraining-neural-network-models/

Great took for neural network, deep learning and machine learning models visualization. https://github.com/lutzroeder/netron

Super VIP Cheatsheet: Deep Learning