Machine learning projects
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Machine Learning Projects
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Python projects
Machine Learning projects
Machine Learning projects
Speech Emotion Recognition Python
ABOUT:
Speech Emotion Recognition (SER) is the task of recognizing the emotion from speech irrespective of the semantic contents. However, emotions are subjective and even for humans it is hard to notate them in natural speech communication regardless of the meaning.
TECHNOLOGIES:
- python
- Djnago
- Machine learning
- html
- css
- js
Age and Gender Detection
ABOUT:
Age and gender detection using machine learning is a popular computer vision application. It involves training models to accurately predict the age and gender of individuals based on facial features. These models leverage deep learning algorithms and large datasets to achieve high accuracy. By analyzing facial characteristics, such as wrinkles, contours, and facial hair, machine learning algorithms can provide valuable insights for various applications, including demographic analysis, targeted marketing, and personalized user experiences.
TECHNOLOGIES:
- python
- Tkinter
- Machine learning
Real Time Face mask Recognition OpenCV
ABOUT:
Live mask prediction using machine learning is an emerging application in computer vision. It involves training models to detect whether individuals are wearing masks in real-time video streams. These models utilize deep learning techniques and image processing algorithms to identify facial regions and classify them as masked or unmasked. Live mask prediction can be valuable for enforcing safety measures, monitoring public spaces, and implementing automated mask compliance systems.
TECHNOLOGIES:
- python
- Djnago
- Machine learning
- html
- css
- js
YouTube video summarization using machine learning
ABOUT:
YouTube video summarization using machine learning is a cutting-edge technique that automates the process of extracting key information from videos. By leveraging advanced algorithms, it can analyze video content, identify important segments, and generate concise summaries. This technology has the potential to save time for viewers, enhance content accessibility, and enable efficient video browsing and indexing.
TECHNOLOGIES:
- python
- Djnago
- Machine learning
- html
- css
- js
Traffic sign classification
ABOUT:
Traffic sign recognition is a vital application of computer vision and machine learning in the field of transportation. By training models on large datasets, it enables automatic detection and classification of traffic signs, aiding in road safety and driver assistance systems. This technology can accurately identify signs such as speed limits, stop signs, and warning signs, contributing to efficient navigation and reducing the risk of accidents.
TECHNOLOGIES:
- python
- Tkinter
- Machine learning
Noise suppression using machine learning
ABOUT:
Noise suppression using machine learning is a powerful technique that reduces unwanted background noise from audio signals. By training models on diverse noise patterns, it can accurately distinguish between noise and desired audio, enhancing speech quality and intelligibility. This technology finds applications in various domains, such as voice communication, audio recordings, and speech recognition systems, improving the overall user experience and enabling clearer audio communication in noisy environments.
TECHNOLOGIES:
- python
- Djnago
- Machine learning
- html
- css
- js