Implement Image Recognition with a Convolutional Neural Network

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Pratheerth Padman

1:05:04

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1. Course Overview

1. Course Overview.mp4

02:03

2. Exploring and Preparing a Dataset for Image Recognition

1. Course and Module Introduction.mp4

02:55

2. What Are We Trying to Solve.mp4

03:28

3. Demo - Setting up Your Environment.mp4

02:50

4. Demo - Organizing the Dataset.mp4

04:54

5. Demo - Exploring the Dataset.mp4

03:26

7. Summary and Up Next.mp4

01:03

03. Training a Convolutional Neural Network to Classify Images

01. Module Introduction.mp4

00:58

02. What Are Convolutional Neural Networks.mp4

02:21

03. CNN - Convolutions.mp4

04:46

04. CNN - Activation.mp4

04:50

05. CNN - Pooling.mp4

01:38

06. CNN - Classification.mp4

01:01

07. Demo - Creating the CNN Architecture.mp4

05:18

08. Demo - Training the Model.mp4

01:57

10. Summary and Up Next.mp4

01:13

04. Improving Performance of the Convolutional Neural Network

01. Module Introduction.mp4

01:20

02. Better Performance When and How.mp4

02:09

04. Hyperparameter Tuning.mp4

03:29

05. Overfitting and Underfitting.mp4

03:24

07. What Is Transfer Learning.mp4

04:20

08. Transfer Learning When and How.mp4

04:18

10. Summary.mp4

01:23

Description

Image recognition is used in a wide variety of ways in our daily lives. This course will teach you how to tune and implement convolutional neural networks in order to implement image recognition and classification on a business case.

What You'll Learn?

Image recognition has an extensive and important impact on our daily lives. From unlocking phones using facial recognition to detecting anomalies in chest-x rays, it is everywhere.

In this course, Implement Image Recognition with a Convolutional Neural Network, you’ll understand how to implement image recognition and classification on your very own dataset.

First, you’ll be introduced to the problem and dataset. Then, you’ll learn how to explore and prepare the dataset for the next step. Next, you’ll see how to build, train, and test a neural network on the dataset. Finally, you’ll explore how image augmentation and transfer learning help to lift the performance metrics involved in your solution.

When you’re finished with this course, you’ll have the knowledge required to implement image recognition on any dataset of your choice.

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Neural Networks

Pratheerth Padman

Instructor's Courses

Pratheerth is a Data Scientist who has entered the field after an eclectic mix of educational and work experiences. He has a Bachelor's in Engineering in Mechatronics from India, Masters in Engineering Management from Australia and then a couple of years of work experience as a Production Engineer in the Middle East. Then when the A.I bug bit him, he dropped everything to dedicate his life to the field. He is currently working on mentoring, course creation and freelancing as a Data Scientist.

Pluralsight

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Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.