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Sign Language Detection Using Action Recognition with Python - LSTM Deep Learning Model

Nicholas Renotte via YouTube

Overview

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This course shows how to build a real-time sign language detection system in Python. Learners extract MediaPipe Holistic keypoints, collect and preprocess video sequences, train an LSTM model with TensorFlow and Keras, evaluate it, and make webcam predictions.

Syllabus

- Start
- Gameplan
- How it Works
- Tutorial Start
- 1. Install and Import Dependencies
- 2. Detect Face, Hand and Pose Landmarks
- 3. Extract Keypoints
- 4. Setup Folders for Data Collection
- 5. Collect Keypoint Sequences
- 6. Preprocess Data and Create Labels
- 7. Build and Train an LSTM Deep Learning Model
- 8. Make Sign Language Predictions
- 9. Save Model Weights
- 10. Evaluation using a Confusion Matrix
- 11. Test in Real Time
- BONUS: Improving Performance
- Wrap Up

Taught by

Nicholas Renotte

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