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Machine Learning with Python

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

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📈 Telegram kanali Machine Learning with Python analitikasi

Machine Learning with Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 68 471 obunachidan iborat bo'lib, Taʼlim toifasida 2 400-o'rinni va Hindiston mintaqasida 4 598-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 68 471 obunachiga ega bo‘ldi.

31 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 12 ga, so‘nggi 24 soatda esa -24 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 3.99% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.46% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 2 735 marta ko‘riladi; birinchi sutkada odatda 998 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 8 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 01 Noyabr, 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.

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68 471
Obunachilar
-2424 soatlar
-947 kun
+1230 kun
Postlar arxiv
Awesome interactive textbook on probability theory and statistics Inside are clear visualizations, interactive elements, and minimal dry theory. You can tweak distributions, sample datasets, play with confidence intervals, and clearly see how it all works Get it here, I recommend opening it on a desktop https://seeing-theory.brown.edu/ 👉 @DataScienceM

Repost from Machine Learning
📌 Extracting Structured Vehicle Data from Images 🗂 Category: 🕒 Date: 2025-01-27 | ⏱️ Read time: 10 min read Build an Autom
📌 Extracting Structured Vehicle Data from Images 🗂 Category: 🕒 Date: 2025-01-27 | ⏱️ Read time: 10 min read Build an Automated Vehicle Documentation System that Extracts Structured Information from Images, using OpenAI API,…

Awesome interactive textbook on probability theory and statistics Inside are clear visualizations, interactive elements, and minimal dry theory. You can tweak distributions, sample datasets, play with confidence intervals, and clearly see how it all works Get it here, I recommend opening it on a desktop https://seeing-theory.brown.edu/ 👉 @DataScienceM

Repost from Machine Learning
Awesome interactive textbook on probability theory and statistics Inside are clear visualizations, interactive elements, and minimal dry theory. You can tweak distributions, sample datasets, play with confidence intervals, and clearly see how it all works Get it here, I recommend opening it on a desktop https://seeing-theory.brown.edu/ 👉 @DataScienceM I spent years chasing success until I found the 7 daily habits no one talks about—now everything’s changed for me. Most people miss the real secret. See what you’ve been overlooking: Success Tips 🔥 | InsideAds

Repost from Machine Learning
📌 How to Build a Genetic Algorithm from Scratch in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-30 | ⏱️ Read time: 16 m
📌 How to Build a Genetic Algorithm from Scratch in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-30 | ⏱️ Read time: 16 min read A complete walkthrough on how one can build a Genetic Algorithm from scratch in Python,…

Python library RetinaFace for face detection and working with key points (eyes, nose, mouth) Supports face alignment, easily
Python library RetinaFace for face detection and working with key points (eyes, nose, mouth) Supports face alignment, easily installed via pip install retina-face, and works based on deep models from the insightface project. An excellent tool for tasks in computer vision and face recognition. Usage examples:
from retinaface import RetinaFace

resp = RetinaFace.detect_faces("img1.jpg")
print(resp)

{
    "face_1": {
        "score": 0.9993440508842468,
        "facial_area": [155, 81, 434, 443],
        "landmarks": {
          "right_eye": [257.82974, 209.64787],
          "left_eye": [374.93427, 251.78687],
          "nose": [303.4773, 299.91144],
          "mouth_right": [228.37329, 338.73193],
          "mouth_left": [320.21982, 374.58798]
        }
  }
}
👉 @DataScienceN

Creating QR codes with Python in just a few lines of code Anyone can generate their own QR code for a link, text, or even Wi-
Creating QR codes with Python in just a few lines of code Anyone can generate their own QR code for a link, text, or even Wi-Fi data. For this, the qrcode library and the PIL module are used
pip install qrcode pillow
import qrcode
from PIL import Image

data = input("Enter data for QR: ")
qr = qrcode.QRCode(version=3, box_size=8, border=4)
qr.add_data(data)
qr.make(fit=True)

image = qr.make_image(fill="black", back_color="aqua")
image.save("qr_code.png")
Image.open("qr_code.png")
The output is a ready QR code with any text or link. You can change colors, sizes, and style to fit your design 🙂 👉 https://t.me/CodeProgrammer

Repost from Machine Learning
📌 A Guide to Clustering Algorithms 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-06 | ⏱️ Read time: 6 min read An overview of c
📌 A Guide to Clustering Algorithms 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-06 | ⏱️ Read time: 6 min read An overview of clustering and the different families of clustering algorithms.

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Repost from Machine Learning
📌 Image Segmentation With K-Means Clustering 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-05 | ⏱️ Read time: 11 min read A
📌 Image Segmentation With K-Means Clustering 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-05 | ⏱️ Read time: 11 min read An introduction with Python

Google Collab notebooks to learn everything you need to master prompt engineering with Claude - from basic structure and role
Google Collab notebooks to learn everything you need to master prompt engineering with Claude - from basic structure and role prompting to advanced techniques like few-shot learning, avoiding hallucinations, and tool use. Perfect interactive lessons to level up your AI skills Link: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P

Soon 😉

Think trading is all about luck or chasing fast money? The truth is much simpler: real results come from steady discipline, s
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Our paid channel contains more than 9000 books and 500 paid courses With a $3 monthly subscription, you can cancel whenever you want https://t.me/+r_Tcx2c-oVU1OWNi

Harvard's "Advanced Algorithms" by Jelani Nelson 📽 Lecture Videos: https://youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayh
Harvard's "Advanced Algorithms" by Jelani Nelson 📽 Lecture Videos: https://youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf 📷 Lecture Notes: https://people.seas.harvard.edu/~cs224/fall14/lec.html

Today I am 3️⃣0️⃣ years old, I am excited to make more successes and achievements My previous year was full of exciting events and economic, political and programmatic noise, but I kept moving forward Best regards Eng. @HusseinSheikho 🔤

“Nobody believed you could grow small capital—until I saw this.” $1,000 turned into real profit before my eyes. The secret? B
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“Nobody believed I could double my deposit safely… But inside Elite Gold Trading, we proved it: real people, real profits, re
“Nobody believed I could double my deposit safely… But inside Elite Gold Trading, we proved it: real people, real profits, real discipline. Want to see how our members avoid big losses and keep winning? 👉 Discover the secret inside #ad InsideAds

Repost from Machine Learning
📌 A Basic Introduction to Quantum GANs 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read “Quantu
📌 A Basic Introduction to Quantum GANs 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read “Quantum computing just becomes vastly simpler once you take the physics out of it.”