Computer vision, especially Image Classification, is one of the most exciting areas of AI and Machine learning with ground-breaking real-world applications. As part of the TensorFlow Developer certification, this course focuses on image classification leveraging the TensorFlow framework. In this course, TensorFlow Developer Certificate – Image Classification, you’ll gain the ability to build, train, evaluate, and tune computer vision neural network models using the TensorFlow framework. First, you’ll explore computer vision and its application and how Convolutional Neural Networks can be built and used for image classification use cases. Next, you’ll discover techniques and TensorFlow components for handling complex and real-world images, such as ImageGenerator and image augmentation. Finally, you’ll learn how to apply transfer learning techniques to improve model performance and extend the binary classification setup to multi-class classification problems. When you’re finished with this course, you’ll have the skills and knowledge of TensorFlow components needed to build computer vision neural works for image classification.
Author Name: Abhishek Kumar
Author Description:
Abhishek Kumar is a data science consultant, author, and Google Developers Expert (GDE) in machine learning. He holds a master’s degree from the University of California, Berkeley, and has been featured in the “Top 40 under 40 Data Scientist” list. He is also a public speaker and has delivered talks in top data conferences across the globe including Strata Data, AI conference, ODSC, and Fifth Elephant. His focus area is machine learning and deep learning at scale and is also a recipient of the… more

Table of Contents

• Course Overview
  1min
• Getting Started With Computer Vision
  35mins
• Understanding Convolutional Neural Networks
  29mins
• Dealing with Real-world Images
  39mins
• Applying Transfer Learning
  20mins
• Creating Multi-class Classification Model
  22mins
• Summary
  6mins