Image Recognition with Machine Learning

Gain insights into image data processing and CNNs for image classification using TensorFlow. Delve into CNN architectures and their applications, requiring Python and TensorFlow knowledge.

Advanced

45 Lessons

Certificate of Completion

Gain insights into image data processing and CNNs for image classification using TensorFlow. Delve into CNN architectures and their applications, requiring Python and TensorFlow knowledge.

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Explanations

AI-POWERED

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This course includes

17 Playgrounds

27 Challenges

This course includes

17 Playgrounds

27 Challenges

Course Overview

If you want to dive into the technology behind computer vision and self driving cars, this is where to start. In this course you'll learn how to process data from image files and create convolutional neural networks (CNNs) to classify different types of images. After completing this course, you will have a solid understanding of why CNNs work and which CNN architectures to use for different tasks. The code for this course is built around the TensorFlow framework, one of the premier frameworks for industry...Show More

Course Content

What you'll learn from this course

Get familiar with image recognition using CNN, including data preparation and augmentation.

Overview

Image Processing

Walk through image processing techniques for model preparation using TensorFlow and Pillow.

Introduction

Image Files Image Types Resizing Dataset Iterator Execution PIL Library Quiz

CNN

Master the steps to recognize handwritten digits using convolutional neural networks.

Introduction

Initialization Reshaping Convolution Max Pooling Multiple Layers Fully-Connected Dropout Logits Classification Quiz

SqueezeNet

Enhance your skills in developing efficient, high-performance image recognition models with SqueezeNet.

Introduction

Initialization Augmentation Fire Module Stacking Fire Model Layers Adding Fire Depth Logits Sparse Labels Quiz

ResNet

Deepen your knowledge of ResNet architecture, focusing on residual learning for enhanced deep network performance.

Introduction ImageNet Initialization Padding Pre-activation Shortcut ResNet Block Bottleneck Block Layer Model Layers Full Model Architecture Quiz Course Conclusion

Course Author

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Add a deep mastery of ML to your skillset, and make yourself a more in-demand developer.

Become a Machine Learning Engineer

This Skill Path covers Python fundamentals, machine learning techniques and algorithms through practical exercises, preparing you as a machine learning engineer for real-world applications.

12 Modules

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