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Machine Learning with Python
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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho
Ko'proq ko'rsatish📈 Telegram kanali Machine Learning with Python analitikasi
Machine Learning with Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 67 813 obunachidan iborat bo'lib, Taʼlim toifasida 2 427-o'rinni va Hindiston mintaqasida 5 028-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 67 813 obunachiga ega bo‘ldi.
13 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 60 ga, so‘nggi 24 soatda esa -3 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 4.31% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.69% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 926 marta ko‘riladi; birinchi sutkada odatda 1 148 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 6 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent insidead, learning, degree, evaluation, algorithm kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 14 Iyun, 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.
67 813
Obunachilar
-324 soatlar
-77 kunlar
+6030 kunlar
Postlar arxiv
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Some Helpful Data Science Projects for Beginners
https://www.kaggle.com/c/house-prices-advanced-regression-techniques
https://www.kaggle.com/c/digit-recognizer
https://www.kaggle.com/c/titanic
Intermediate Level Data science Projects
Black Friday Data : https://www.kaggle.com/sdolezel/black-friday
Human Activity Recognition Data : https://www.kaggle.com/uciml/human-activity-recognition-with-smartphones
Trip History Data : https://www.kaggle.com/pronto/cycle-share-dataset
Million Song Data : https://www.kaggle.com/c/msdchallenge
Census Income Data : https://www.kaggle.com/c/census-income/data
Movie Lens Data : https://www.kaggle.com/grouplens/movielens-20m-dataset
Twitter Classification Data : https://www.kaggle.com/c/twitter-sentiment-analysis2
Text mining : https://www.kaggle.com/kanncaa1/applying-text-mining
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Repost from Machine Learning
Are you fluent in Python and want to evaluate your skills? 🤔
Do you want to learn Python? 🤗
Are you interested in learning through questions and answers? 😵
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✅ Learn PyTorch in 4 steps
👨🏻💻 With support for more than 200 different mathematical operations, PyTorch is one of the most powerful open source and computational libraries based on Python for machine learning. You don't need to look for different sources to learn this popular library, but the website of this library covers more than what you need.💯
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⬅️ Topics: tensors, datasets and DataLoader, model building, optimization loop, saving, loading and using the model.
📄 PyTorch Basics
┘📎 Link: Learn the Basics
2️⃣ Video training: This section is very useful for those who prefer video content.
⬅️ Topics: introduction, tensor construction and model construction with pytorch.
📄 Introduction to PyTorch
┘📎 Link: Introduction to PyTorch
3️⃣ Examining examples: By viewing different examples, you will review what you have learned so far.
📄 Learning Python by example
┘📎 Link: Learning PyTorch with Examples
4️⃣ Coding: This step is vital! Your theoretical knowledge is worthless without coding! The Keras website is full of sample code that is great for getting started.
📄 Start coding
┘📎 Link: keras.io
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Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
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7️⃣ Deep Learning
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Repost from Python Courses & Resources
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🔥 Large selection of interview questions on DS, AI, ML, DL, NLP, computer vision . Part 2
✅ Machine learning interview questions and answers for data scientists
✅ Deep Learning Interview Questions and Answers for Data Scientists
✅ Statistics questions
✅ Questions on probability theory
✅ Repository for a line of online courses on statistics
✅ Questions and answers for data scientists in Python
✅ SQL and DB Interview Questions and Answers for Data Scientists
Questions Based on Resumes
✅ Large Language Model (LLM) Interview Questions and Answers
✅ Questions and answers to interviews on computer vision part 1
✅ Computer vision interview questions and answers part 2
✅ Questions and answers to computer vision interviews part 3
