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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

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网络: Machine Learning with Python印度4 586教育2 406...

📈 Telegram 频道 Machine Learning with Python 的分析概览

频道 Machine Learning with Python (@codeprogrammer) 英语语言赛道中的是活跃参与者。目前社区聚集了 68 482 名订阅者，在教育类别中位列第 2 406，并在印度地区排名第 4 586 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 68 482 名订阅者。

根据 04 十一月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 -75，过去 24 小时变化为 7，整体触达仍然可观。

认证状态： 未认证
互动率 (ER)： 平均受众互动率为 3.38%。内容发布后 24 小时内通常能获得 1.57% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 2 314 次浏览，首日通常累积 1 073 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 9。
主题关注点： 内容集中在 insidead, learning, degree, evaluation, algorithm 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

凭借高频更新（最新数据采集于 05 十一月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为教育类别中的关键影响点。

Buy Ad

68 482

订阅者

+724 小时

-597 天

-7530 天

2 314

帖子浏览量

~ 1 07324 小时

~ 1 59648 小时

3.38%

参与率

~ 2

每日帖子数

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帖子存档

68 482

Deep Learning NLP AI Python ML Data Mining Tensorflow Keras 👇👇👇👇👇 @Machine_learn

68 482

-2147483648_-216077.webp0.45 KB

68 482

Repost from Machine Learning with Python

This channels is for Programmers, Coders, Software Engineers. 0- Python 1- Data Science 2- Machine Learning 3- Data Visualization 4- Artificial Intelligence 5- Data Analysis 6- Statistics 7- Deep Learning 8- programming Languages https://t.me/addlist/8_rRW2scgfRhOTc0

68 482

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68 482

Repost from Machine Learning with Python

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🖥 Unraveling the Magic of Sorting: A Python Guide for Novices ▪Bubble Sort

def bubble_sort(list):
    for i in range(len(list)):
        for j in range(len(list) - 1):
            if list[j] > list[j + 1]:
                list[j], list[j + 1] = list[j + 1], list[j] # swap
    return list

▪Selection Sort

def selection_sort(list):
    for i in range(len(list)):
        min_index = i
        for j in range(i + 1, len(list)):
            if list[min_index] > list[j]:
                min_index = j
        list[i], list[min_index] = list[min_index], list[i] # swap
    return list

▪Insertion Sort

def insertion_sort(list):
    for i in range(1, len(list)):
        key = list[i]
        j = i - 1
        while j >=0 and key < list[j] :
            list[j+1] = list[j]
            j -= 1
        list[j+1] = key
    return list

▪Quick Sort

def partition(array, low, high):
    i = (low-1)
    pivot = array[high]

    for j in range(low, high):
        if array[j] <= pivot:
            i = i+1
            array[i], array[j] = array[j], array[i]
    array[i+1], array[high] = array[high], array[i+1]
    return (i+1)

def quick_sort(array, low, high):
    if len(array) == 1:
        return array
    if low < high:
        partition_index = partition(array, low, high)
        quick_sort(array, low, partition_index-1)
        quick_sort(array, partition_index+1, high)

https://t.me/CodeProgrammer

68 482

Repost from AI & ML Papers

🖥 10 Advanced Python Scripts For Everyday Programming 1. SpeedTest with Python


# pip install pyspeedtest
# pip install speedtest
# pip install speedtest-cli

#method 1
import speedtest

speedTest = speedtest.Speedtest()
print(speedTest.get_best_server())

#Check download speed
print(speedTest.download())

#Check upload speed
print(speedTest.upload())

# Method 2

import pyspeedtest
st = pyspeedtest.SpeedTest()
st.ping()
st.download()
st.upload()

2. Search on Google

# pip install google

from googlesearch import search

query = "Medium.com"

for url in search(query):
    print(url)

3. Make Web Bot

# pip install selenium

import time
from selenium import webdriver
from selenium.webdriver.common.keys import Keys

bot = webdriver.Chrome("chromedriver.exe")
bot.get('[http://www.google.com'](http://www.google.com'))

search = bot.find_element_by_name('q')
search.send_keys("@codedev101")
search.send_keys(Keys.RETURN)
time.sleep(5)
bot.quit()

4. Fetch Song Lyrics

# pip install lyricsgenius

import lyricsgenius

api_key = "xxxxxxxxxxxxxxxxxxxxx"

genius = lyricsgenius.Genius(api_key)
artist = genius.search_artist("Pop Smoke", max_songs=5,sort="title")
song = artist.song("100k On a Coupe")

print(song.lyrics)

5. Get Exif Data of Photos

# Get Exif of Photo

# Method 1
# pip install pillow
import PIL.Image
import PIL.ExifTags

img = PIL.Image.open("Img.jpg")
exif_data =
{
    PIL.ExifTags.TAGS[i]: j
    for i, j in img._getexif().items()
    if i in PIL.ExifTags.TAGS
}
print(exif_data)


# Method 2
# pip install ExifRead
import exifread

filename = open(path_name, 'rb')

tags = exifread.process_file(filename)
print(tags)

6. OCR Text from Image

# pip install pytesseract

import pytesseract
from PIL import Image

pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'

t=Image.open("img.png")
text = pytesseract.image_to_string(t, config='')

print(text)

7. Convert Photo into Cartonize

# pip install opencv-python

import cv2

img = cv2.imread('img.jpg')
grayimg = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
grayimg  = cv2.medianBlur(grayimg, 5)

edges = cv2.Laplacian(grayimg , cv2.CV_8U, ksize=5)
r,mask =cv2.threshold(edges,100,255,cv2.THRESH_BINARY_INV)

img2 = cv2.bitwise_and(img, img, mask=mask)
img2 = cv2.medianBlur(img2, 5)

cv2.imwrite("cartooned.jpg", mask)

8. Empty Recycle Bin

# pip install winshell

import winshell
try:
    winshell.recycle_bin().empty(confirm=False, /show_progress=False, sound=True)
    print("Recycle bin is emptied Now")
except:
    print("Recycle bin already empty")

9. Python Image Enhancement

# pip install pillow

from PIL import Image,ImageFilter
from PIL import ImageEnhance

im = Image.open('img.jpg')

# Choose your filter
# add Hastag at start if you don't want to any filter below

en = ImageEnhance.Color(im)
en = ImageEnhance.Contrast(im)
en = ImageEnhance.Brightness(im)
en = ImageEnhance.Sharpness(im)

# result
en.enhance(1.5).show("enhanced")

10. Get Window Version

# Window Version

import wmi
data = wmi.WMI()
for os_name in data.Win32_OperatingSystem():
  print(os_name.Caption) # Microsoft Windows 11 Home

https://t.me/DataScienceT

68 482

Repost from Machine Learning with Python

68 482

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68 482

Deep Learning NLP AI Python ML Data Mining Tensorflow Keras 👇👇👇👇👇 @Machine_learn

68 482

Deep Learning NLP AI Python ML Data Mining Tensorflow Keras 👇👇👇👇👇 @Machine_learn

68 482

Deep Learning NLP AI Python ML Data Mining Tensorflow Keras 👇👇👇👇👇 @Machine_learn

68 482

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68 482

This channel is for Programmers, Coders, Software Engineers. 1- Data Science 2- Machine Learning 3- Data Visualization 4- Artificial Intelligence 5- Data Analysis 6- Statistics 7- Deep Learning https://t.me/DataScienceM https://t.me/DataScienceM