Carl Osipov walks you through creating increasingly sophisticated image classification models using TensorFlow. You’ll learn how to improve your models’ accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while avoiding overfitting your data as you discover how ML is applied to image classification. Along the way, Carl outlines strategies for building an image classifier using convolutional neural networks.
Carl Osipov is a program manager focused on helping Google’s customers and business partners get trained and certified to run machine learning and data analytics workloads on Google Cloud. Carl has more than 16 years of experience in the IT industry and has held leadership roles for programs and projects in the areas of big data, cloud computing, service-oriented architecture, machine learning, and computational natural language processing at some of the world’s leading technology companies across the United States and Europe. Carl has written over 20 articles in professional, trade, and academic journals and holds six patents from the USPTO. He has received three corporate awards from IBM for his innovative work. You can find out more about Carl on his blog.
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@Abdurrahman Thank you for taking the time to attend the session! The Jupyter notebooks you used during the session are available from https://github.com/GoogleCloudPlatform/training-data-analyst/tree/master/bootcamps/imagereco To access the slides, please login back to the Qwiklabs account you created during the session and look under “Lecture Notes”
Dear Carl. Can you please the course materials