Python | Machine Learning | Coding

Python | Machine Learning | Coding | R

How to Make a Twitter Bot in Python With Tweepy

https://realpython.com/twitter-bot-python-tweepy/

✅ More ♥️♥️ = more posts

@CodeProgrammer ♥️

4.4K viewsedited 07:35

Python | Machine Learning | Coding | R

Understanding Simple Recurrent Neural Networks in Keras

https://machinelearningmastery.com/understanding-simple-recurrent-neural-networks-in-keras/

✅ More ♥️♥️ = more posts

@CodeProgrammer ♥️

4.9K viewsedited 17:03

Python | Machine Learning | Coding | R

Python Docker Tutorials

Docker is a containerization tool used for spinning up isolated, reproducible application environments. It is a popular development tool for Python developers.

https://realpython.com/tutorials/docker/

5.0K views06:57

Python | Machine Learning | Coding | R

The Transformer Attention Mechanism

https://machinelearningmastery.com/the-transformer-attention-mechanism/

✅ More ♥️♥️ = more posts

@CodeProgrammer ♥️

4.9K viewsedited 03:30

Python | Machine Learning | Coding | R

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

5.1K views03:50

Python | Machine Learning | Coding | R

Data Version Control With Python and DVC

https://realpython.com/python-data-version-control

@CodeProgrammer ♥️

5.0K viewsedited 05:49

Python | Machine Learning | Coding | R

The Luong Attention Mechanism

https://machinelearningmastery.com/the-luong-attention-mechanism/

@CodeProgrammer

4.7K viewsedited 18:20

Python | Machine Learning | Coding | R

Forwarded from Python | Machine Learning | Coding | R

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

3.4K views20:28

Python | Machine Learning | Coding | R

Forwarded from Data Science | Machine Learning with Python for Researchers

🖥 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

4.5K views07:20

Python | Machine Learning | Coding | R

🖥 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

5.3K viewsedited 11:13

Python | Machine Learning | Coding | R

NumPy Tutorial: Your First Steps Into Data Science in Python

https://realpython.com/numpy-tutorial

https://t.me/CodeProgrammer

5.3K viewsedited 10:28

Python | Machine Learning | Coding | R

Building an Image Recognition API using Flask.

Step 1: Set up the project environment

1. Create a new directory for your project and navigate to it.
2. Create a virtual environment (optional but recommended):
(Image 1.)
3. Install the necessary libraries (image 2.)

Step 2: Create a Flask Web Application
Create a new file called app.py in the project directory (image 3.)

Step 3: Launch the Flask Application
Save the changes and run the Flask application (image 4.)

Step 4: Test the API
Your API is now up and running and you can send images to /predict via HTTP POST requests.
You can use tools such as curl or Postman to test the API.
• An example of using curl (image 5.)
• An example using Python queries (image 6.)

https://t.me/DataScienceT

5.4K views16:43

Python | Machine Learning | Coding | R

📩 Python Email Automation Script

import smtplib
from email.mime.text import MIMEText


sender_email = "your_email@example.com"
recipient_email = "recipient_email@example.com"

subject = "Automated Email"
message = "This is an automated email sent using Python."


# SMTP server configuration (example: Gmail)


smtp_server = "smtp.gmail.com"
smtp_port = 587
smtp_username = "your_username"
smtp_password = "your_password"



msg = MIMEText(message)
msg["Subject"] = subject
msg["From"] = sender_email
msg["To"] = recipient_email
try:

    server = smtplib.SMTP(smtp_server, smtp_port)
    server.starttls()
       server.login(smtp_username, smtp_password)
    server.sendmail(sender_email, recipient_email, msg.as_string())
    print("Email sent successfully!")
    
except Exception as e:
    print("Error sending email:", str(e))
    
finally:

    server.quit()

https://t.me/DataScienceT

5.5K views03:24

Python | Machine Learning | Coding | R

Customize the Django Admin With Python

https://realpython.com/customize-django-admin-python/

https://t.me/CodeProgrammer

5.8K viewsedited 05:27

Python | Machine Learning | Coding | R

5.6K views12:28

Python | Machine Learning | Coding | R

We launched a special bot some time ago to download all scientific, software and mathematics books The bot contains more than thirty million books, and new books are downloaded first, In addition to the possibility of downloading all articles and scientific papers for free

To request a subscription: talk to @Hussein_Sheikho

5.6K views21:52

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