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>Set up an <code>Iterator</code> to extract data from a pixel array dataset</li>
</ul>


<h2>A. Using Iterator</h2>

<div id="section1_l5" class="collapse show">
<p>The way we can extract the decoded image data from our <code>Dataset</code> is through a <code><a href="https://www.tensorflow.org/api_docs/python/tf/data/Iterator" target="_blank">tf.data.Iterator</a></code>. For a more in-depth look at <code>tf.data.Iterator</code>, check out the <a href='https://www.educative.io/collection/6083138522447872/5873588626259968/'>Industry Case Study</a> course on Educative.</p>
<p>We use the <code>get_next</code> function to obtain a <i>next-element tensor</i>, which is used for data extraction. Note that the next-element tensor doesn't have an actual value until we execute the iteration process using <code>tf.compat.v1.Session</code> (see next chapter).</p>
</div>


<h2>Chapter Goals:</h2>
<ul>
	<li>Set up an <code>Iterator</code> to extract data from a pixel array dataset</li>
</ul>


<h2>A. Using Iterator</h2>

<div id="section1_l5">
<p>The way we can extract the decoded image data from our <code>Dataset</code> is through a <code><a href="https://www.tensorflow.org/api_docs/python/tf/data/Iterator" target="_blank">tf.data.Iterator</a></code>. For a more in-depth look at <code>tf.data.Iterator</code>, check out the <a href='https://www.educative.io/collection/6083138522447872/5873588626259968/'>Industry Case Study</a> course on Educative.</p>
<p>We use the <code>get_next</code> function to obtain a <i>next-element tensor</i>, which is used for data extraction. Note that the next-element tensor doesn't have an actual value until we execute the iteration process using <code>tf.compat.v1.Session</code> (see next chapter).</p>
</div>


Set up an Iterator to extract data from an image dataset.

Image Processing

CNN

SqueezeNet

ResNet

Conclusion

Iterator

Chapter Goals:

A. Using Iterator