In lesson 6 of Deep Learning with Python, we discuss Convolutional Neural Networks (CNNs). We understand what they are and then leverage CNN to build an algorithm that can identify from images, whether a car is damaged or not.
You can watch the video of the lesson here:
The dataset for this modeling exercise can be accessed here:
As mentioned in the video, I could not run this in the Anaconda cloud environment as it ran into memory issues with my account. Hence, instead of link, you will have to download this file this week.
Kumar Singh is the founder of Designed Analytics LLC, which is focused on helping organizations explore how to leverage data and analytics to effectively compete, thrive and innovate.
Kumar has over a decade of hands-on experience in supply chain and operations analytics. With over a decade of industry experience, he has worked across multiple industries, helping companies set up analytics centers of excellence.
Post his industry experience, Kumar also did a stint in external consulting as a data science consultant with Boston Consulting Group (BCG). Kumar holds an MSc. in AI from Liverpool John Moores University, a Masters in Supply Chain from The Ross School of Business at The University of Michigan, Ann Arbor, an MBA in Operations Management from IIT Roorkee, India, and an undergraduate degree in Electrical engineering.
Kumar is ASCM CPIM, CSCP, and CLTD certified and holds the PMP certification from PMI. He is also an AWS-certified Machine Learning Specialist and Microsoft certified in the Azure IoT developer specialty.
Designed Analytics Blog 