π₯ Convert PDF to docx using Python
βͺGithub: https://github.com/dothinking/pdf2docx
https://www.tgoop.com/CodeProgrammer
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βͺGithub: https://github.com/dothinking/pdf2docx
https://www.tgoop.com/CodeProgrammer
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π21β€14
π₯ Roadmap of free courses for learning Python and Machine learning.
βͺData Science
βͺ AI/ML
βͺ Web Dev
1. Start with this
https://kaggle.com/learn/python
2. Take any one of these
β― https://openclassrooms.com/courses/6900856-learn-programming-with-python
β― https://scaler.com/topics/course/python-for-beginners/
β― https://simplilearn.com/learn-python-basics-free-course-skillup
3. Then take this
https://netacad.com/courses/programming/pcap-programming-essentials-python
4. Attempt for this certification
https://freecodecamp.org/learn/scientific-computing-with-python/
5. Take it to next level
β― Data Scrapping, NumPy, Pandas
https://scaler.com/topics/course/python-for-data-science/
β― Data Analysis
https://openclassrooms.com/courses/2304731-learn-python-basics-for-data-analysis
β― Data Visualization
https://kaggle.com/learn/data-visualization
β― Django
https://openclassrooms.com/courses/6967196-create-a-web-application-with-django
β― Machine Learning
http://developers.google.com/machine-learning/crash-course
β― Deep Learning (TensorFlow)
http://kaggle.com/learn/intro-to-deep-learning
https://www.tgoop.com/CodeProgrammer
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βͺData Science
βͺ AI/ML
βͺ Web Dev
1. Start with this
https://kaggle.com/learn/python
2. Take any one of these
β― https://openclassrooms.com/courses/6900856-learn-programming-with-python
β― https://scaler.com/topics/course/python-for-beginners/
β― https://simplilearn.com/learn-python-basics-free-course-skillup
3. Then take this
https://netacad.com/courses/programming/pcap-programming-essentials-python
4. Attempt for this certification
https://freecodecamp.org/learn/scientific-computing-with-python/
5. Take it to next level
β― Data Scrapping, NumPy, Pandas
https://scaler.com/topics/course/python-for-data-science/
β― Data Analysis
https://openclassrooms.com/courses/2304731-learn-python-basics-for-data-analysis
β― Data Visualization
https://kaggle.com/learn/data-visualization
β― Django
https://openclassrooms.com/courses/6967196-create-a-web-application-with-django
β― Machine Learning
http://developers.google.com/machine-learning/crash-course
β― Deep Learning (TensorFlow)
http://kaggle.com/learn/intro-to-deep-learning
https://www.tgoop.com/CodeProgrammer
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β€38π12β€βπ₯4π1
ML_cheatsheets.pdf
6.5 MB
Machine Learning cheatsheet (very important)
https://www.tgoop.com/CodeProgrammer
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β€29π8
Python | Machine Learning | Coding | R
β Hand gesture recognition Full Source Code ππππ
β Hand gesture recognition
https://www.tgoop.com/CodeProgrammer
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import cv2
import mediapipe as mp
# Initialize MediaPipe Hands module
mp_hands = mp.solutions.hands
hands = mp_hands.Hands()
# Initialize MediaPipe Drawing module for drawing landmarks
mp_drawing = mp.solutions.drawing_utils
# Open a video capture object (0 for the default camera)
cap = cv2.VideoCapture(0)
while cap.isOpened():
ret, frame = cap.read()
if not ret:
continue
# Convert the frame to RGB format
frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# Process the frame to detect hands
results = hands.process(frame_rgb)
# Check if hands are detected
if results.multi_hand_landmarks:
for hand_landmarks in results.multi_hand_landmarks:
# Draw landmarks on the frame
mp_drawing.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)
# Display the frame with hand landmarks
cv2.imshow('Hand Recognition', frame)
# Exit when 'q' is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Release the video capture object and close the OpenCV windows
cap.release()
cv2.destroyAllWindows()
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π―21π12β€5β€βπ₯2
π Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
https://www.tgoop.com/CodeProgrammer
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The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
https://www.tgoop.com/CodeProgrammer
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β€36π14
Code Stars
Get ahead of the game with Code Stars! Our platform sends you notifications about the hottest GitHub repositories that are rapidly gaining popularity. Don't miss out - join us now and be the first to discover the trending repositories that everyone will be talking about soon!
Get ahead of the game with Code Stars! Our platform sends you notifications about the hottest GitHub repositories that are rapidly gaining popularity. Don't miss out - join us now and be the first to discover the trending repositories that everyone will be talking about soon!
β€15π4π―3
How to Download Files From URLs With Python
https://realpython.com/python-download-file-from-url
https://www.tgoop.com/CodeProgrammer
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https://realpython.com/python-download-file-from-url
https://www.tgoop.com/CodeProgrammer
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β€15π8