Building Image Classification Solutions Using Keras and Transfer Learning
Offered By: Pluralsight
Course Description
Overview
This is a course in which you’ll go all the way from being introduced to image classification to eventually learning how to implement and tune convolutional neural networks.
In a world with ever-expanding, abundant image data, image classification is a low hanging fruit that has found its way to a multitude of applications ranging from manufacturing to healthcare and even security. In this course, Building Image Classification Solutions Using Keras and Transfer Learning, you will learn both about image classification, and how to eventually implement and tune neural networks. First, you will be introduced to the fundamentals of how a neural network works. Next, you will discover the basics of how to build an image classifier – from scratch! Then, you will explore how the researchers from top universities and corporate giants have approached this problem. Next, you will delve into the problem you’ve encountered to their “pre-build” models. Finally, you will be briefed on how to improve the performance of your classifier and the pitfalls you’re likely to encounter while going about building one. When you are finished with this course, you will have a foundational knowledge of image classification that will help you solve your own problems in computer vision.
In a world with ever-expanding, abundant image data, image classification is a low hanging fruit that has found its way to a multitude of applications ranging from manufacturing to healthcare and even security. In this course, Building Image Classification Solutions Using Keras and Transfer Learning, you will learn both about image classification, and how to eventually implement and tune neural networks. First, you will be introduced to the fundamentals of how a neural network works. Next, you will discover the basics of how to build an image classifier – from scratch! Then, you will explore how the researchers from top universities and corporate giants have approached this problem. Next, you will delve into the problem you’ve encountered to their “pre-build” models. Finally, you will be briefed on how to improve the performance of your classifier and the pitfalls you’re likely to encounter while going about building one. When you are finished with this course, you will have a foundational knowledge of image classification that will help you solve your own problems in computer vision.
Syllabus
- Course Overview 1min
- Classifying Images – Overview and Applications 10mins
- Building a Convolutional Neural Network to Classify Images 26mins
- Improving Training and Performance using Transfer Learning 19mins
- Enhancing Performance and Spotting Pitfalls 26mins
Taught by
Pratheerth Padman
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