Face Recognition Service with Python Dlib Flask | Coupon ED
Face Recognition Service with Python Dlib Flask | Coupon ED
Face Recognition Web App with Machine Learning in FLASK 5.0 (2 ratings) Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability,
What you'll learn
In this course, you will learn end to end process and able to build any artificial intelligence Project. Starting from
For the preprocess images, we will extract features from the images, ie. computing Eigen images using principal component analysis. With Eigen images, we will train the Machine learning model and also learn to test our model before deploying, to get the best results from the model we will tune with Grid search method for best hyperparameters.
Once our machine learning model is ready, will we learn and develop web server gateway interphase in flask by rendering HTML CSS and bootstrap in the frontend and in the backend written in Python. Finally, we will create the project on the Face Recognition project by integrating the machine learning model to Flask App.
Face Recognition Web App with Machine Learning in FLASK 5.0 (2 ratings) Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability,
What you'll learn
- Automatic Face Recognition in images and videos
- Automatically detect faces from images and videos
- Evaluate and Tune Machine Learning
- Building Machine Learning Model for Classification
- Make Pipeline Model for deploying your application
- Image Processing with OpenCV
- Data Preprocessing for Images
- Create REST APIs in Flask
- Template Inheritance in Flask
- Integrating Machine Learning Model in Flask App
In this course, you will learn end to end process and able to build any artificial intelligence Project. Starting from
- Gathering the data,
- Data Understanding
- Data Preprocessing
- Data Analysis
- Predictive Modelling
- Create REST APIs in Flask
For the preprocess images, we will extract features from the images, ie. computing Eigen images using principal component analysis. With Eigen images, we will train the Machine learning model and also learn to test our model before deploying, to get the best results from the model we will tune with Grid search method for best hyperparameters.
Once our machine learning model is ready, will we learn and develop web server gateway interphase in flask by rendering HTML CSS and bootstrap in the frontend and in the backend written in Python. Finally, we will create the project on the Face Recognition project by integrating the machine learning model to Flask App.
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