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Master Machine Learning & Neural Networks for Data Science and Computer Vision
Updated on Sep, 2026
Programming, Data Science, Deep Learning
Duration - 3.5 hours
Training 5 or more people ?
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In this self-paced course, you will learn how to use Tensorflow 2 to build convolutional neural networks (CNNs). We'll take an in-depth look at what convolution is, why it is useful, and how to integrate it into a neural network. We'll apply CNNs to several practical image recognition datasets, from small and relatively simple to large and complex. We'll learn about techniques that help to improve performance, such as batch normalization, data augmentation, and transfer learning. The course includes video presentations, coding lessons, hands-on exercises, and links to further resources.
This course is intended for:
Suggested prerequisites:
In this course, we will cover:
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