Benoit Dherin explains how machine learning is applied to image classification, discusses evolving methods and challenges, and walks you through creating increasingly sophisticated image classification models using TensorFlow. You’ll learn different strategies for building an image classifier using convolutional neural networks and discover how to improve the model’s accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while avoiding overfitting your data.
Benoit Dherin is a machine learning solutions engineer at Google’s Advanced Solutions Lab, where he teaches machine learning to Google clients and helps them implement machine learning solutions in the Google Cloud. Previously, Benoit held roles in data science, machine learning, and software engineering at various companies and startups in Silicon Valley as well as research and teaching positions at universities around the world. Benoit holds a PhD in mathematics from ETH Zurich. In his free time, he enjoys reading, traveling, and doing Bikram Yoga.
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