Learn machine learning algorithms for image recognition, which is used in various applications in computer vision and self-driving cars.

Neural Networks: Beginners to Advanced

If you want to dive into the technology behind computer vision and self-driving cars, this is where to start. In this module, you'll learn how to process data from image files and create convolutional neural networks (CNNs) to classify different types of images. 

The code for this module is built around the TensorFlow framework, one of the premier frameworks for industry machine learning, and the Python pandas library for data analysis. Knowledge of Python and TensorFlow are prerequisites. 

After completing this module, you will have a solid understanding of why CNNs work and which CNN architectures to use for different tasks.

Neural Networks for Image Recognition

<h2 class="section-title">Chapter Goals:</h2>
<ul>
	<li>Learn about image data and pixels</li>
	<li>Read byte data from an image file</li>
</ul>



<h2>A. Image data</h2>

<div id="section1_l1" class="collapse show">
<p>Before we do any image processing, we need to understand how image files work. Specifically, we'll discuss how these files use byte data and pixels to represent images.</p>
<p>If you've ever looked at an image file's properties before, it'll show the dimensions of the image, i.e. the height and width of the image. The height and width are based on number of pixels. For example, if the dimensions of an image are 400x300 (width x height), then the total number of pixels in the image is 120000.</p>
</div>


<h2>Chapter Goals:</h2>
<ul>
	<li>Learn about image data and pixels</li>
	<li>Read byte data from an image file</li>
</ul>



<h2>A. Image data</h2>

<div id="section1_l1">
<p>Before we do any image processing, we need to understand how image files work. Specifically, we'll discuss how these files use byte data and pixels to represent images.</p>
<p>If you've ever looked at an image file's properties before, it'll show the dimensions of the image, i.e. the height and width of the image. The height and width are based on number of pixels. For example, if the dimensions of an image are 400x300 (width x height), then the total number of pixels in the image is 120000.</p>
</div>


Discover how image data is stored in files and how pixels affect image interpretation.

Image Processing

CNN

SqueezeNet

ResNet

Conclusion

Image Files

Chapter Goals:

A. Image data