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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

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Machinelearning (@ai_machinelearning_big_data) Rus til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 293 167 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 326-o'rinni va Rossiya mintaqasida 1 276-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 293 167 obunachiga ega bo‘ldi.

04 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -6 366 ga, so‘nggi 24 soatda esa -131 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 7.35% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 5.62% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 21 569 marta ko‘riladi; birinchi sutkada odatda 16 480 ta ko‘rish yig‘iladi.
Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 168 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 05 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.

293 167

Obunachilar

-13124 soatlar

-1 4647 kunlar

-6 36630 kunlar

21 569

Post ko'rishlar

~ 16 48024 soatlar

~ 18 29048 soatlar

7.35%

Muloqot nisbati

~ 6

Kuniga postlar

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Postlar arxiv

293 155

Synthetic Celebrity Faces at 128x128 Resolution After Tuning Generated by the Progressive Growing GAN How to Train a Progressive Growing GAN in Keras for Synthesizing Faces https://machinelearningmastery.com/how-to-train-a-progressive-growing-gan-in-keras-for-synthesizing-faces/

293 155

Accelerated CNN Training Through Gradient Approximation https://arxiv.org/abs/1908.05460

293 155

Освойте самую востребованную технологию искусственного интеллекта! У вас уже есть базовое понимание машинного обучения и знание языка Python? Повысьте компетенции и получите практические навыки по программированию глубоких нейронных сетей! В SkillFactory открыт новый набор на курс "Deep Learning и нейронные сети" https://clc.to/6onwXA разработанный при поддержке NVIDIA Corporation. Проекты, над которыми вы будете работать, включают: ● создание нейронной сети для распознавания рукописных цифр; ● обучение рекурентной сети задачам прогнозирования временных рядов; ● разработку нейросетевого чат-бота; ● создание модели для идентификации лиц и генерации лиц на основе архитектуры GAN; ● разработку агента для игры на основе DQN алгоритма. Вы познакомитесь с основными библиотеками для Deep Learning, такими как TensorFlow, Keras и другими. 🔥 Жаркая новость: супер-скидки Августа -30%, узнайте подробности: https://clc.to/6onwXA

293 155

Awesome Machine Learning A curated list of awesome machine learning frameworks, libraries and software (by language). libraries: https://github.com/josephmisiti/awesome-machine-learning books: https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md

293 155

How technology impacts the way of producing and consuming food at AGRO & TECH conference by Sistema_VC Founders of startups from the UK, the Netherlands and Russia will talk about how AI provides people with better nutrition and globally helps fighting hunger. You will learn how agriculture and tech interact and network with startup founders, innovation managers, investors and the media in the industry. Place: Moscow, Kollektiv Space, Bol'shoy Znamenskiy 2s3, metro Kropotkinskaya Date: August 21st, 6 pm Register free: https://is.gd/JgvmUA

293 155

How vFlat used the TFLite GPU delegate for real time inference to scan books https://medium.com/tensorflow/how-vflat-used-the-tflite-gpu-delegate-for-real-time-inference-to-scan-books-df3bb86a4eb7

293 155

New advances in natural language processing to better connect people https://ai.facebook.com/blog/new-advances-in-natural-language-processing-to-better-connect-people

293 155

VisualBERT: A Simple and Performant Baseline for Vision and Language https://arxiv.org/abs/1908.03557

293 155

How to Implement Progressive Growing GAN Models in Keras https://machinelearningmastery.com/how-to-implement-progressive-growing-gan-models-in-keras/

293 155

Project Euphonia’s Personalized Speech Recognition for Non-Standard Speech http://ai.googleblog.com/2019/08/project-euphonias-personalized-speech.html

293 155

Collaborative Multi-Agent Dialogue Model Training Via Reinforcement Learning https://eng.uber.com/research/collaborative-multi-agent-dialogue-model-training-via-reinforcement-learning/ article: https://arxiv.org/pdf/1907.05507.pdf

293 155

The Best of AI: New Articles Published This Month (July 2019) https://blog.sicara.com/07-2019-best-ai-new-articles-this-month-3e1fa3f6c321

293 155

A Finnish News Corpus for Named Entity Recognition https://arxiv.org/abs/1908.04212

293 155

New paper on training with pseudo-labels for semantic segmentation Semi-Supervised Segmentation of Salt Bodies in Seismic Images: SOTA (1st place) at TGS Salt Identification Challenge. Github: https://github.com/ybabakhin/kaggle_salt_bes_phalanx ArXiV: https://arxiv.org/abs/1904.04445 #GCPR2019 #Segmentation #CV

293 155

A Gentle Introduction to the Progressive Growing GAN https://machinelearningmastery.com/introduction-to-progressive-growing-generative-adversarial-networks/

293 155

LVIS: A Dataset for Large Vocabulary Instance Segmentation https://arxiv.org/abs/1908.03195

293 155

A new model for word embeddings that are resilient to misspellings https://ai.facebook.com/blog/-a-new-model-for-word-embeddings-that-are-resilient-to-misspellings-/ https://github.com/facebookresearch/moe?fbclid=IwAR3pCHx4-8oWTqgYqUnKHxcVWdDzPuOVTL0sTidyDBX9J7UPt2HcWxRG9AA

293 155

NeuPDE: Neural Network Based Ordinary and Partial Differential Equations for Modeling Time-Dependent Data https://arxiv.org/abs/1908.03190

293 155

How to Develop a CycleGAN for Image-to-Image Translation with Keras https://machinelearningmastery.com/cyclegan-tutorial-with-keras/

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Interpreting Latent Space of GANs for Semantic Face Editing https://shenyujun.github.io/InterFaceGAN/ code: https://github.com/ShenYujun/InterFaceGAN.git