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🦙 Code Llama
The most powerful AI assistant for writing Python code.
• Github: https://github.com/facebookresearch/codellama
• Docs: https://ai.meta.com/blog/code-llama-large-language-model-coding/
• Post: https://ai.meta.com/blog/code-llama-large-language-model-coding/
https://t.me/CodeProgrammer
The most powerful AI assistant for writing Python code.
• Github: https://github.com/facebookresearch/codellama
• Docs: https://ai.meta.com/blog/code-llama-large-language-model-coding/
• Post: https://ai.meta.com/blog/code-llama-large-language-model-coding/
https://t.me/CodeProgrammer
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👁Savant: Supercharged Computer Vision and Video Analytics Framework on DeepStream
▪Github: https://github.com/insight-platform/Savant
https://t.me/CodeProgrammer
git clone https://github.com/insight-platform/Savant.git
cd Savant/samples/peoplenet_detector
git lfs pull▪Github: https://github.com/insight-platform/Savant
https://t.me/CodeProgrammer
🖥 Convert PDF to docx using Python
▪Github: https://github.com/dothinking/pdf2docx
https://t.me/CodeProgrammer
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▪Github: https://github.com/dothinking/pdf2docx
https://t.me/CodeProgrammer
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🖥 Roadmap of free courses for learning Python and Machine learning.
▪Data Science
▪ AI/ML
▪ Web Dev
1. Start with this
https://kaggle.com/learn/python
2. Take any one of these
❯ https://openclassrooms.com/courses/6900856-learn-programming-with-python
❯ https://scaler.com/topics/course/python-for-beginners/
❯ 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
❯ Data Scrapping, NumPy, Pandas
https://scaler.com/topics/course/python-for-data-science/
❯ Data Analysis
https://openclassrooms.com/courses/2304731-learn-python-basics-for-data-analysis
❯ Data Visualization
https://kaggle.com/learn/data-visualization
❯ Django
https://openclassrooms.com/courses/6967196-create-a-web-application-with-django
❯ Machine Learning
http://developers.google.com/machine-learning/crash-course
❯ Deep Learning (TensorFlow)
http://kaggle.com/learn/intro-to-deep-learning
https://t.me/CodeProgrammer
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▪Data Science
▪ AI/ML
▪ Web Dev
1. Start with this
https://kaggle.com/learn/python
2. Take any one of these
❯ https://openclassrooms.com/courses/6900856-learn-programming-with-python
❯ https://scaler.com/topics/course/python-for-beginners/
❯ 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
❯ Data Scrapping, NumPy, Pandas
https://scaler.com/topics/course/python-for-data-science/
❯ Data Analysis
https://openclassrooms.com/courses/2304731-learn-python-basics-for-data-analysis
❯ Data Visualization
https://kaggle.com/learn/data-visualization
❯ Django
https://openclassrooms.com/courses/6967196-create-a-web-application-with-django
❯ Machine Learning
http://developers.google.com/machine-learning/crash-course
❯ Deep Learning (TensorFlow)
http://kaggle.com/learn/intro-to-deep-learning
https://t.me/CodeProgrammer
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ML_cheatsheets.pdf
6.5 MB
Machine Learning cheatsheet (very important)
https://t.me/CodeProgrammer
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Python | Machine Learning | Coding | R
✋ Hand gesture recognition Full Source Code 👇👇👇👇
✋ Hand gesture recognition
https://t.me/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()https://t.me/CodeProgrammer
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📈 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
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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://t.me/CodeProgrammer
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