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Machine learning books and papers

Machine learning books and papers

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📈 Telegram kanali Machine learning books and papers analitikasi

Machine learning books and papers (@machine_learn) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 24 510 obunachidan iborat bo'lib, Taʼlim toifasida 8 033-o'rinni va Eron mintaqasida 13 749-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 24 510 obunachiga ega bo‘ldi.

03 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -99 ga, so‘nggi 24 soatda esa 2 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 6.54% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.24% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 1 603 marta ko‘riladi; birinchi sutkada odatda 549 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 1 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent disorder, psy, مقاله, framework, graph kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Admin: @Raminmousa ID: @Machine_learn link: https://t.me/Machine_learn

Yuqori yangilanish chastotasi (oxirgi ma’lumot 04 Iyul, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

24 510
Obunachilar
+224 soatlar
-107 kunlar
-9930 kunlar
Postlar arxiv
✅ مروری مختصر بر مباحثی که در دوره ي تخصصی " پیاده سازی شبکه های عصبی در متلب" آموزش داده خواهد شد. تئوری ➕ پیاده‌سازی ➕ پروژه عملی مدرس: محمد نوری زاده چرلو فارغ التحصیل دانشگاه علم و صنعت تهران #شبکه_عصبی #دوره #پروژه_محور #کلاسبندی #پیشبینی #خوشه_بندی #کاهش_بعد #مدلسازی #استخراج_ویژگی #تئوری #پیاده_سازی #پروژه_عملی #mlp #perceptron #rbf #elm #pnn #som #recurrent #jordan #elman ظرفیت باقی مانده: 4 نفر زمان برگزاری: چهارشنبه ها (هر جلسه 5 ساعت ) مدت دوره: 25 ساعت جهت کسب اطلاعات بیشتر با شماره زیر تماس بگیرید: 0936-038-2687 @onlinebme_admin 🏢 آکادمی آنلاین مهندسی پزشکی و هوش مصنوعی https://telegram.me/joinchat/BcXDaEEL4FjSZ9Uxrki-9Q

#Investigating Capsule Networks with Dynamic Routing for Text Classification #paper @Machine_learn

#Investigating Capsule Networks with Dynamic Routing for Text Classification #paper @Machine_learn
#Investigating Capsule Networks with Dynamic Routing for Text Classification #paper @Machine_learn

#Python Projects for Kids — Jessica Ingrassellino (en) 2016 #book #python #beginner @Machine_learn

#Python Projects for Kids — Jessica Ingrassellino (en) 2016 #book #python #beginner @Machine_learn
#Python Projects for Kids — Jessica Ingrassellino (en) 2016 #book #python #beginner @Machine_learn

#Machine learning in scikit-learn #python library #tutorial @machine_learn http://gaelvaroquaux.github.com/scikit-learn-tutor
#Machine learning in scikit-learn #python library #tutorial @machine_learn http://gaelvaroquaux.github.com/scikit-learn-tutorial/

#Deep Learning Papers Reading Roadmap #Roadmap #deeplearning #papers @Machine_learn http://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap

#Deep Learning #NATURE #paper @Machine_learn

#Segmentation of bone structure in X-ray images using #convolutional neural network #CNN #DL #Xray #image_classification @Machine_learn

discriminative : 1:#Regression 2:#Logistic regression 3:#decision tree(Hunt) 4:#neural network(traditional network, deep netw
discriminative : 1:#Regression 2:#Logistic regression 3:#decision tree(Hunt) 4:#neural network(traditional network, deep network) 5:#Support Vector Machine(SVM) Generative: 1:#Hidden Markov model 2:#Naive bayes 3:#K-nearest neighbor(KNN) 4:#Generative adversarial networks(GANs) Deep learning: 1:CNN 2:RNN 3:LSTM 4:CapsuleNet 5:Siamese: siamese cnn siamese lstm siamese bi-lstm siamese CapsuleNet 6:time series data جهت درخواست و راهنمایی در رابطه با پیاده سازی مقالات و پایان نامه ها در رابطه با مباحث deep learning و machine learning با ایدی زیر در ارتباط باشید @Raminmousa

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

#From Attention in Transformers to Dynamic Routing in Capsule Nets #CapsuleNet #Dynamic_Routing @Machine_learn https://staff.
#From Attention in Transformers to Dynamic Routing in Capsule Nets #CapsuleNet #Dynamic_Routing @Machine_learn https://staff.fnwi.uva.nl/s.abnar/?p=108

#Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to #Deep Learning #book @Machine_learn

#Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to #Deep Learning #book @Machine_learn
#Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to #Deep Learning #book @Machine_learn

#Hot topic for project, thesis, and research – Machine Learning #thesis #research #DL @Machine_learn https://www.techsparks.c
#Hot topic for project, thesis, and research – Machine Learning #thesis #research #DL @Machine_learn https://www.techsparks.co.in/hot-topic-for-project-and-thesis-machine-learning/

#Sentiment Analysis approaches #single domain and multi-domain #slide #Author:@Raminmousa @Machine_learn

#Sentiment Analysis approaches #single domain and multi-domain #slide #Author:@Raminmousa @Machine_learn
#Sentiment Analysis approaches #single domain and multi-domain #slide #Author:@Raminmousa @Machine_learn

#Introduction To Machine Learning classification and clustering #slide #Author:@Raminmousa @Machine_learn