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- Start
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- Loading Image paths into tf.data
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- Loading, Scaling and Resizing Images in a pipeline
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- Creating Positive and Negative Samples
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- Caching, Batching and Splitting the Pipeline
Description:
Learn how to build a deep facial recognition application for authentication in this comprehensive video tutorial. Explore the process of preparing data for deep learning using TensorFlow Dataloader. Discover techniques for scaling and resizing images as part of a deep learning pipeline, loading and labelling images efficiently, and splitting data pipelines into training and testing partitions. Follow along as the instructor demonstrates implementing facial recognition based on the Siamese Neural Networks for One-shot Image Recognition paper. Gain hands-on experience with loading image paths into tf.data, creating positive and negative samples, and optimizing your pipeline through caching and batching. Access the provided code repository and additional resources to enhance your understanding of facial recognition technology and its practical applications in authentication systems.

Build a Deep Facial Recognition App - Preparing Data for Deep Learning - TF Dataloader

Nicholas Renotte
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