Machine Learning
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Real Machine Learning — simple, practical, and built on experience.
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Face Recognition with Local Binary Patterns (LBPs) and OpenCV

📖 In this tutorial, you will learn how to perform face recognition using Local Binary Patterns (LBPs), OpenCV, and the cv2.face.LBPHFaceRecognizer_create function. In our previous tutorial, we discussed the fundamentals of face recognition, including: The difference between face detection and face…...

🏷️ #FaceApplications #OpenCVTutorials #Tutorials
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Face detection tips, suggestions, and best practices

📖 In this tutorial, you will learn my tips, suggestions, and best practices to achieve high face detection accuracy with OpenCV and dlib. We’ve covered face detection four times on the PyImageSearch blog: Face detection with OpenCV and Haar cascades Face…...

🏷️ #FaceApplications #OpenCVTutorials #Tutorials
Breaking captchas with deep learning, Keras, and TensorFlow

📖 In the past, we’ve worked with datasets that have been pre-compiled and labeled for us — but what if we wanted to go about creating our own custom dataset and then training a CNN on it? In this tutorial, I’ll…...

🏷️ #DeepLearning #KerasandTensorFlow #Tutorials
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Smile detection with OpenCV, Keras, and TensorFlow

📖 In this tutorial, we will be building a complete end-to-end application that can detect smiles in a video stream in real-time using deep learning along with traditional computer vision techniques. To accomplish this task, we’ll be training the LetNet architecture…...

🏷️ #DeepLearning #KerasandTensorFlow #Tutorials
Data augmentation with tf.data and TensorFlow

📖 In this tutorial, you will learn two methods to incorporate data augmentation into your tf.data pipeline using Keras and TensorFlow. A good dataset of images is vital when working with data augmentation in TensorFlow. It enables us to see how…...

🏷️ #DeepLearning #KerasandTensorFlow #Tutorials
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